This paper proposes linear and nonlinear filters for a non-Gaussian dynamic system with an unknown nominal covariance of the output noise.The challenge of designing a suitable filter in the presence of an unknown cova...This paper proposes linear and nonlinear filters for a non-Gaussian dynamic system with an unknown nominal covariance of the output noise.The challenge of designing a suitable filter in the presence of an unknown covariance matrix is addressed by focusing on the output data set of the system.Considering that data generated from a Gaussian distribution exhibit ellipsoidal scattering,we first propose the weighted sum of norms(SON)clustering method that prioritizes nearby points,reduces distant point influence,and lowers computational cost.Then,by introducing the weighted maximum likelihood,we propose a semi-definite program(SDP)to detect outliers and reduce their impacts on each cluster.Detecting these weights paves the way to obtain an appropriate covariance of the output noise.Next,two filtering approaches are presented:a cluster-based robust linear filter using the maximum a posterior(MAP)estimation and a clusterbased robust nonlinear filter assuming that output noise distribution stems from some Gaussian noise resources according to the ellipsoidal clusters.At last,simulation results demonstrate the effectiveness of our proposed filtering approaches.展开更多
The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recogni...The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.展开更多
In this study,a fifth-degree cubature particle filter(5CPF)is proposed to address the limited estimation accuracy in traditional particle filter algorithms for bearings-only tracking(BOT).This algorithm calculates the...In this study,a fifth-degree cubature particle filter(5CPF)is proposed to address the limited estimation accuracy in traditional particle filter algorithms for bearings-only tracking(BOT).This algorithm calculates the recommended density function by introducing a fifth-degree cubature Kalman filter algorithm to guide particle sampling,which effectively alleviates the problem of particle degradation and significantly improves the estimation accuracy of the filter.However,the 5CPF algorithm exhibits high computational complexity,particularly in scenarios with a large number of particles.Therefore,we propose the extended Kalman filter(EKF)-5CPF algorithm,which employs an EKF to replace the time update step for each particle in the 5CPF.This enhances the algorithm’s real-time capability while maintaining the high precision advantage of the 5CPF algorithm.In addition,we construct bearing-only dual-station and single-motion station target tracking systems,and the filtering performances of 5CPF and EKF-5CPF algorithms under different conditions are analyzed.The results show that both the 5CPF algorithm and EKF-5CPF have strong robustness and can adapt to different noise environments.Furthermore,both algorithms significantly outperform traditional nonlinear filtering algorithms in terms of convergence speed,tracking accuracy,and overall stability.展开更多
In the globalized market environment, increasingly significant economic and environmental factors withincomplex industrial plants impose importance on the optimization of global production indices; such opti-mization ...In the globalized market environment, increasingly significant economic and environmental factors withincomplex industrial plants impose importance on the optimization of global production indices; such opti-mization includes improvements in production efficiency, product quality, and yield, along with reductionsof energy and resource usage. This paper briefly overviews recent progress in data-driven hybrid intelli-gence optimization methods and technologies in improving the performance of global production indicesin mineral processing. First, we provide the problem description. Next, we summarize recent progress indata-based optimization for mineral processing plants. This optimization consists of four layers： optimiza-tion of the target values for monthly global production indices, optimization of the target values for dailyglobal production indices, optimization of the target values for operational indices, and automation systemsfor unit processes. We briefly overview recent progress in each of the different layers. Finally, we point outopportunities for future works in data-based optimization for mineral processing plants.展开更多
In this paper,a data-based scheme is proposed to solve the optimal tracking problem of autonomous nonlinear switching systems.The system state is forced to track the reference signal by minimizing the performance func...In this paper,a data-based scheme is proposed to solve the optimal tracking problem of autonomous nonlinear switching systems.The system state is forced to track the reference signal by minimizing the performance function.First,the problem is transformed to solve the corresponding Bellman optimality equation in terms of the Q-function(also named as action value function).Then,an iterative algorithm based on adaptive dynamic programming(ADP)is developed to find the optimal solution which is totally based on sampled data.The linear-in-parameter(LIP)neural network is taken as the value function approximator.Considering the presence of approximation error at each iteration step,the generated approximated value function sequence is proved to be boundedness around the exact optimal solution under some verifiable assumptions.Moreover,the effect that the learning process will be terminated after a finite number of iterations is investigated in this paper.A sufficient condition for asymptotically stability of the tracking error is derived.Finally,the effectiveness of the algorithm is demonstrated with three simulation examples.展开更多
In this paper, a data-based fault tolerant control(FTC) scheme is investigated for unknown continuous-time(CT)affine nonlinear systems with actuator faults. First, a neural network(NN) identifier based on particle swa...In this paper, a data-based fault tolerant control(FTC) scheme is investigated for unknown continuous-time(CT)affine nonlinear systems with actuator faults. First, a neural network(NN) identifier based on particle swarm optimization(PSO) is constructed to model the unknown system dynamics. By utilizing the estimated system states, the particle swarm optimized critic neural network(PSOCNN) is employed to solve the Hamilton-Jacobi-Bellman equation(HJBE) more efficiently.Then, a data-based FTC scheme, which consists of the NN identifier and the fault compensator, is proposed to achieve actuator fault tolerance. The stability of the closed-loop system under actuator faults is guaranteed by the Lyapunov stability theorem. Finally, simulations are provided to demonstrate the effectiveness of the developed method.展开更多
This paper focuses on developing a system that allows presentation authors to effectively retrieve presentation slides for reuse from a large volume of existing presentation materials. We assume episodic memories of t...This paper focuses on developing a system that allows presentation authors to effectively retrieve presentation slides for reuse from a large volume of existing presentation materials. We assume episodic memories of the authors can be used as contextual keywords in query expressions to efficiently dig out the expected slides for reuse rather than using only the part-of-slide-descriptions-based keyword queries. As a system, a new slide repository is proposed, composed of slide material collections, slide content data and pieces of information from authors＇ episodic memories related to each slide and presentation together with a slide retrieval application enabling authors to use the episodic memories as part of queries. The result of our experiment shows that the episodic memory-used queries can give more discoverability than the keyword-based queries. Additionally, an improvement model is discussed on the slide retrieval for further slide-finding efficiency by expanding the episodic memories model in the repository taking in the links with the author-and-slide-related data and events having been post on the private and social media sites.展开更多
The surge of large-scale models in recent years has led to breakthroughs in numerous fields,but it has also introduced higher computational costs and more complex network architectures.These increasingly large and int...The surge of large-scale models in recent years has led to breakthroughs in numerous fields,but it has also introduced higher computational costs and more complex network architectures.These increasingly large and intricate networks pose challenges for deployment and execution while also exacerbating the issue of network over-parameterization.To address this issue,various network compression techniques have been developed,such as network pruning.A typical pruning algorithm follows a three-step pipeline involving training,pruning,and retraining.Existing methods often directly set the pruned filters to zero during retraining,significantly reducing the parameter space.However,this direct pruning strategy frequently results in irreversible information loss.In the early stages of training,a network still contains much uncertainty,and evaluating filter importance may not be sufficiently rigorous.To manage the pruning process effectively,this paper proposes a flexible neural network pruning algorithm based on the logistic growth differential equation,considering the characteristics of network training.Unlike other pruning algorithms that directly reduce filter weights,this algorithm introduces a three-stage adaptive weight decay strategy inspired by the logistic growth differential equation.It employs a gentle decay rate in the initial training stage,a rapid decay rate during the intermediate stage,and a slower decay rate in the network convergence stage.Additionally,the decay rate is adjusted adaptively based on the filter weights at each stage.By controlling the adaptive decay rate at each stage,the pruning of neural network filters can be effectively managed.In experiments conducted on the CIFAR-10 and ILSVRC-2012 datasets,the pruning of neural networks significantly reduces the floating-point operations while maintaining the same pruning rate.Specifically,when implementing a 30%pruning rate on the ResNet-110 network,the pruned neural network not only decreases floating-point operations by 40.8%but also enhances the classification accuracy by 0.49%compared to the original network.展开更多
To cope with the challenges of CoViD-19,europe has adopted relevant measures of a data-based approach to governance,on which scholars have huge differences,and the related researches are conducive to further discussio...To cope with the challenges of CoViD-19,europe has adopted relevant measures of a data-based approach to governance,on which scholars have huge differences,and the related researches are conducive to further discussion on the differences.By sorting out the challenges posed by the pandemic to public security and data protection in europe,we can summarize the“european Solution”of the data-based approach to governance,including legislation,instruments,supervision,international cooperation,and continuity.The“Solution”has curbed the spread of the pandemic to a certain extent.However,due to the influence of the traditional values of the EU,the“Solution”is too idealistic in the balance between public security and data protection,which intensifies the dilemma and causes many problems,such as ambiguous legislation,inadequate effectiveness and security of instruments,an arduous endeavor in inter national cooperation,and imperfect regulations on digital green certificates.Therefore,in a major public health crisis,there is still a long way to go in exploring a balance between public security and data protection.展开更多
In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenario...In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenarios with non-Gaussian noise and heavy-tailed outliers.The proposed design modifies the extended Kalman filter(EKF)for the global navigation satellite system(GNSS),integrating the maximum correntropy criterion(MCC)and the variational Bayesian(VB)method.This adaptive algorithm effectively reduces non-line-of-sight(NLOS)reception contamination and improves estimation accuracy,particularly in time-varying GNSS measurements.Experimental results show that the proposed method significantly outperforms conventional approaches in estimation accuracy under heavy-tailed outliers and non-Gaussian noise.By combining MCC with VB approximation for real-time noise covariance estimation using fixed-point iteration,the VBMCEKF achieves superior filtering performance in challenging GNSS conditions.The method’s adaptability and precision make it ideal for improving satellite navigation performance in stochastic environments.展开更多
The integration of surface filtration and catalytic decomposition functions in catalytic bags enables the synergistic removal of multiple pollutants(such as dust,nitrogen oxide,acid gases,and dioxins)in a single react...The integration of surface filtration and catalytic decomposition functions in catalytic bags enables the synergistic removal of multiple pollutants(such as dust,nitrogen oxide,acid gases,and dioxins)in a single reactor,thus effectively reducing the cost and operational difficulties associated with flue gas treatment.In this study,Mn-Ce-Sm-Sn(MCSS)catalysts were prepared and loaded onto hightemperature resistant polyimide(P84)filter through ultrasonic impregnation to create composite catalytic filter.The results demonstrate that the NO conversion rates of the composite catalytic filter consistently achieve above 95%within the temperature range of 160-260℃,with a chlorobenzene T_(90)value of 230℃.The ultrasonic impregnation method effectively loaded the catalyst onto the filter,ensuring high dispersion both on the surface and inside the filter.This increased exposure of catalyst active sites enhances the catalytic activity of the composite catalytic filter.Additionally,increasing the catalyst loading leads to a gradual decrease in permeability,an increase in pressure drops and the long residence time of the flue gas,thereby improving catalytic activity.Compared to ordinary impregnation methods,ultrasonic impregnation improves the bonding strength between the catalyst and filter,as well as the permeability of the composite catalytic filter under the same loading conditions.Overall,this study presents a novel approach to prepare composite catalytic filter for the simultaneous removal of NO and chlorobenzene at low temperatures.展开更多
A medical image encryption is proposed based on the Fisher-Yates scrambling,filter diffusion and S-box substitution.First,chaotic sequence associated with the plaintext is generated by logistic-sine-cosine system,whic...A medical image encryption is proposed based on the Fisher-Yates scrambling,filter diffusion and S-box substitution.First,chaotic sequence associated with the plaintext is generated by logistic-sine-cosine system,which is used for the scrambling,substitution and diffusion processes.The three-dimensional Fisher-Yates scrambling,S-box substitution and diffusion are employed for the first round of encryption.The chaotic sequence is adopted for secondary encryption to scramble the ciphertext obtained in the first round.Then,three-dimensional filter is applied to diffusion for further useful information hiding.The key to the algorithm is generated by the combination of hash value of plaintext image and the input parameters.It improves resisting ability of plaintext attacks.The security analysis shows that the algorithm is effective and efficient.It can resist common attacks.In addition,the good diffusion effect shows that the scheme can solve the differential attacks encountered in the transmission of medical images and has positive implications for future research.展开更多
Brackish water(BW)irrigation may cause soil quality deterioration and thereby a decrease in crop yields.Here we examined the impacts of applying gasification filter cake(GFC),intercropping with Portulaca oleracea(PO),...Brackish water(BW)irrigation may cause soil quality deterioration and thereby a decrease in crop yields.Here we examined the impacts of applying gasification filter cake(GFC),intercropping with Portulaca oleracea(PO),and their combination on soil quality,nutrient uptake by plants and tomato yields under BW irrigation.The treatments evaluated included(i)freshwater irrigation(Control),(ii)BW irrigation,(iii)GFC application under BW irrigation(BW+GFC),(iv)intercropping with PO under BW irrigation(BW+PO),and(v)the combined application of GFC and PO under BW irrigation(BW+PO+GFC).Overall,the use of BW for irrigation resulted in a decline in both soil quality(assessed by a soil quality index(SQI)integrating a wide range of key soil properties including salinity,nutrient availability and microbial activities)and crop yields.Nevertheless,when subjected to BW irrigation,the application of GFC successfully prevented soil salinity.Additionally,the intercropping of PO decreased the soil sodium adsorption ratio and improved the absorption of nutrients by plants.As a result,the BW+GFC+PO treatment generally showed higher tomato yield as compared to other BW-related treatments(i.e.BW,BW+GFC and BW+PO).Compared to BW,the BW+GFC+PO treatment had an average increase of 24.7% in the total fruit yield of four Cropping Seasons.Furthermore,the BW+GFC+PO treatment consistently exhibited the highest fruit quality index(FQI).Taken together,the combined application of GFC and PO is effective in promoting soil quality and crop yields under BW irrigation.展开更多
Fault detection in industrial robot drive systems is a critical aspect of ensuring operational reliability and efficiency.To address the challenge of balancing accuracy and robustness in existing fault detection metho...Fault detection in industrial robot drive systems is a critical aspect of ensuring operational reliability and efficiency.To address the challenge of balancing accuracy and robustness in existing fault detection methods,this paper proposes an enhanced fault detection method based on the unscented Kalman filter(UKF).A comprehensive mathematical model of the brushless DC motor drive system is developed to provide a theoretical foundation for the design of subsequent fault detection methods.The conventional UKF estimation process is detailed,and its limitations in balancing estimation accuracy and robustness are addressed by introducing a dynamic,time-varying boundary layer.To further enhance detection performance,the method incorporates residual analysis using improved z-score and signal-tonoise ratio(SNR)metrics.Numerical simulations under both fault-free and faulty conditions demonstrate that the proposed approach achieves lower root mean square error(RMSE)in fault-free scenarios and provides reliable fault detection.These results highlight the potential of the proposed method to enhance the reliability and robustness of fault detection in industrial robot drive systems.展开更多
The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this paper.First,a comprehensive nonlinear mathematical model that encompasses ...The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this paper.First,a comprehensive nonlinear mathematical model that encompasses both matched and mismatched disturbances is formulated.Due to the fact that only position information can be measured,a linear Extended State Observer(ESO)is introduced to estimate unknown states and matched disturbances,while a dedicated disturbance observer is constructed to estimate mismatched disturbances.Different from the traditional observer results,the design of the disturbance observer used in this study is carried out under the constraint of output feedback.Furthermore,an output feedback nonlinear controller is proposed leveraging the aforementioned observers to achieve accurate trajectory tracking.To mitigate the inherent differential explosion problem of the traditional backstepping framework,a finite-time stable command filter is incorporated.Simultaneously,considering transient filtering errors,a set of error compensation signals are designed to counter their negative impact effectively.Theoretical analysis affirms that the proposed control strategy ensures the boundedness of all signals within the closed-loop system.Additionally,under the specific condition of only time-invariant disturbances in the system,the conclusion of asymptotic stability is established.Finally,the algorithm’s efficacy is validated through comparative experiments.展开更多
Terrain Aided Navigation(TAN)technology has become increasingly important due to its effectiveness in environments where Global Positioning System(GPS)is unavailable.In recent years,TAN systems have been extensively r...Terrain Aided Navigation(TAN)technology has become increasingly important due to its effectiveness in environments where Global Positioning System(GPS)is unavailable.In recent years,TAN systems have been extensively researched for both aerial and underwater navigation applications.However,many TAN systems that rely on recursive Unmanned Aerial Vehicle(UAV)position estimation methods,such as Extended Kalman Filters(EKF),often face challenges with divergence and instability,particularly in highly non-linear systems.To address these issues,this paper proposes and investigates a hybrid two-stage TAN positioning system for UAVs that utilizes Particle Filter.To enhance the system’s robustness against uncertainties caused by noise and to estimate additional system states,a Fuzzy Particle Filter(FPF)is employed in the first stage.This approach introduces a novel terrain composite feature that enables a fuzzy expert system to analyze terrain non-linearities and dynamically adjust the number of particles in real-time.This design allows the UAV to be efficiently localized in GPS-denied environments while also reducing the computational complexity of the particle filter in real-time applications.In the second stage,an Error State Kalman Filter(ESKF)is implemented to estimate the UAV’s altitude.The ESKF is chosen over the conventional EKF method because it is more suitable for non-linear systems.Simulation results demonstrate that the proposed fuzzy-based terrain composite method achieves high positional accuracy while reducing computational time and memory usage.展开更多
In this paper, the problem of cubature Kalman fusion filtering(CKFF) is addressed for multi-sensor systems under amplify-and-forward(AaF) relays. For the purpose of facilitating data transmission, AaF relays are utili...In this paper, the problem of cubature Kalman fusion filtering(CKFF) is addressed for multi-sensor systems under amplify-and-forward(AaF) relays. For the purpose of facilitating data transmission, AaF relays are utilized to regulate signal communication between sensors and filters. Here, the randomly varying channel parameters are represented by a set of stochastic variables whose occurring probabilities are permitted to exhibit bounded uncertainty. Employing the spherical-radial cubature principle, a local filter under AaF relays is initially constructed. This construction ensures and minimizes an upper bound of the filtering error covariance by designing an appropriate filter gain. Subsequently, the local filters are fused through the application of the covariance intersection fusion rule. Furthermore, the uniform boundedness of the filtering error covariance's upper bound is investigated through establishing certain sufficient conditions. The effectiveness of the proposed CKFF scheme is ultimately validated via a simulation experiment concentrating on a three-phase induction machine.展开更多
A novel substrate integrated microstrip to ultra-thin cavity filter transition operating in the W-band is proposed in this letter.The structure is a new method of connecting microstrip circuits and waveguide filters,a...A novel substrate integrated microstrip to ultra-thin cavity filter transition operating in the W-band is proposed in this letter.The structure is a new method of connecting microstrip circuits and waveguide filters,and this new structure enables a planar integrated transition from microstrip lines to ultra-thin cavity filters,thereby reducing the size of the transition structure and achieving miniaturization.The structure includes a conventional tapered microstrip transition structure,which guides the electromagnetic field from the microstrip line to the reduced-height dielectric-filled waveguide,and an air-filled matching cavity which is placed between the dielectric-filled waveguide and the ultra-thin cavity filter.The heights of the microstrip line,the dielectric-filled waveguide and the ultra-thin cavity filter are the same,enabling seamless integration within a planar radio-frequency(RF)circuit.To facilitate testing,mature finline transition structures are integrated at both ends of the microstrip line during fabrications.The simulation results of the fabricated microstrip to ultra-thin cavity filter transition with the finline transition structure,with a passband of 91.5-96.5 GHz,has an insertion loss of less than 1.9 dB and a return loss lower than-20 dB.And the whole structure has also been measured which achieves an insertion loss less than 2.6 dB and a return loss lower than-15 dB within the filter's passband,including the additional insertion loss introduced by the finline transitions.Finally,a W-band compact up-conversion module is designed,and the test results show that after using the proposed structure,the module achieves 95 dBc suppression of the 84 GHz local oscillator.It is also demonstrated that the structure proposed in this letter achieves miniaturization of the system integration without compromising the filter performance.展开更多
Filter capacitors play an important role in altern-ating current(AC)-line filtering for stabilizing voltage,sup-pressing harmonics,and improving power quality.However,traditional aluminum electrolytic capacitors(AECs)...Filter capacitors play an important role in altern-ating current(AC)-line filtering for stabilizing voltage,sup-pressing harmonics,and improving power quality.However,traditional aluminum electrolytic capacitors(AECs)suffer from a large size,short lifespan,low power density,and poor reliability,which limits their use.In contrast,ultrafast supercapacitors(SCs)are ideal for replacing commercial AECs because of their extremely high power densities,fast charging and discharging,and excellent high-frequency re-sponse.We review the design principles and key parameters for ultrafast supercapacitors and summarize research pro-gress in recent years from the aspects of electrode materials,electrolytes,and device configurations.The preparation,structures,and frequency response performance of electrode materials mainly consisting of carbon materials such as graphene and carbon nanotubes,conductive polymers,and transition metal compounds,are focused on.Finally,future research directions for ultrafast SCs are suggested.展开更多
Dear Editor,This letter presents an improved repetitive controller(IRC) that uses a complex-coefficient filter to enhance the tracking performance of a system for periodic signals. Compared with the low-pass filter us...Dear Editor,This letter presents an improved repetitive controller(IRC) that uses a complex-coefficient filter to enhance the tracking performance of a system for periodic signals. Compared with the low-pass filter used in the conventional repetitive controller(CRC), the complex-coefficient filter causes less change in the phase and amplitude of a signal at the frequencies of the periodic signal, especially at the fundamental frequency, when the two filters have the same cutofffrequency.展开更多
文摘This paper proposes linear and nonlinear filters for a non-Gaussian dynamic system with an unknown nominal covariance of the output noise.The challenge of designing a suitable filter in the presence of an unknown covariance matrix is addressed by focusing on the output data set of the system.Considering that data generated from a Gaussian distribution exhibit ellipsoidal scattering,we first propose the weighted sum of norms(SON)clustering method that prioritizes nearby points,reduces distant point influence,and lowers computational cost.Then,by introducing the weighted maximum likelihood,we propose a semi-definite program(SDP)to detect outliers and reduce their impacts on each cluster.Detecting these weights paves the way to obtain an appropriate covariance of the output noise.Next,two filtering approaches are presented:a cluster-based robust linear filter using the maximum a posterior(MAP)estimation and a clusterbased robust nonlinear filter assuming that output noise distribution stems from some Gaussian noise resources according to the ellipsoidal clusters.At last,simulation results demonstrate the effectiveness of our proposed filtering approaches.
文摘The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.
基金Supported by the Guangxi Special Program for Technological Innovation Guidance(No.GuiKeAC25069006).
文摘In this study,a fifth-degree cubature particle filter(5CPF)is proposed to address the limited estimation accuracy in traditional particle filter algorithms for bearings-only tracking(BOT).This algorithm calculates the recommended density function by introducing a fifth-degree cubature Kalman filter algorithm to guide particle sampling,which effectively alleviates the problem of particle degradation and significantly improves the estimation accuracy of the filter.However,the 5CPF algorithm exhibits high computational complexity,particularly in scenarios with a large number of particles.Therefore,we propose the extended Kalman filter(EKF)-5CPF algorithm,which employs an EKF to replace the time update step for each particle in the 5CPF.This enhances the algorithm’s real-time capability while maintaining the high precision advantage of the 5CPF algorithm.In addition,we construct bearing-only dual-station and single-motion station target tracking systems,and the filtering performances of 5CPF and EKF-5CPF algorithms under different conditions are analyzed.The results show that both the 5CPF algorithm and EKF-5CPF have strong robustness and can adapt to different noise environments.Furthermore,both algorithms significantly outperform traditional nonlinear filtering algorithms in terms of convergence speed,tracking accuracy,and overall stability.
文摘In the globalized market environment, increasingly significant economic and environmental factors withincomplex industrial plants impose importance on the optimization of global production indices; such opti-mization includes improvements in production efficiency, product quality, and yield, along with reductionsof energy and resource usage. This paper briefly overviews recent progress in data-driven hybrid intelli-gence optimization methods and technologies in improving the performance of global production indicesin mineral processing. First, we provide the problem description. Next, we summarize recent progress indata-based optimization for mineral processing plants. This optimization consists of four layers： optimiza-tion of the target values for monthly global production indices, optimization of the target values for dailyglobal production indices, optimization of the target values for operational indices, and automation systemsfor unit processes. We briefly overview recent progress in each of the different layers. Finally, we point outopportunities for future works in data-based optimization for mineral processing plants.
基金supported by the National Natural Science Foundation of China(61921004,U1713209,61803085,and 62041301)。
文摘In this paper,a data-based scheme is proposed to solve the optimal tracking problem of autonomous nonlinear switching systems.The system state is forced to track the reference signal by minimizing the performance function.First,the problem is transformed to solve the corresponding Bellman optimality equation in terms of the Q-function(also named as action value function).Then,an iterative algorithm based on adaptive dynamic programming(ADP)is developed to find the optimal solution which is totally based on sampled data.The linear-in-parameter(LIP)neural network is taken as the value function approximator.Considering the presence of approximation error at each iteration step,the generated approximated value function sequence is proved to be boundedness around the exact optimal solution under some verifiable assumptions.Moreover,the effect that the learning process will be terminated after a finite number of iterations is investigated in this paper.A sufficient condition for asymptotically stability of the tracking error is derived.Finally,the effectiveness of the algorithm is demonstrated with three simulation examples.
基金supported in part by the National Natural ScienceFoundation of China(61533017,61973330,61773075,61603387)the Early Career Development Award of SKLMCCS(20180201)the State Key Laboratory of Synthetical Automation for Process Industries(2019-KF-23-03)。
文摘In this paper, a data-based fault tolerant control(FTC) scheme is investigated for unknown continuous-time(CT)affine nonlinear systems with actuator faults. First, a neural network(NN) identifier based on particle swarm optimization(PSO) is constructed to model the unknown system dynamics. By utilizing the estimated system states, the particle swarm optimized critic neural network(PSOCNN) is employed to solve the Hamilton-Jacobi-Bellman equation(HJBE) more efficiently.Then, a data-based FTC scheme, which consists of the NN identifier and the fault compensator, is proposed to achieve actuator fault tolerance. The stability of the closed-loop system under actuator faults is guaranteed by the Lyapunov stability theorem. Finally, simulations are provided to demonstrate the effectiveness of the developed method.
文摘This paper focuses on developing a system that allows presentation authors to effectively retrieve presentation slides for reuse from a large volume of existing presentation materials. We assume episodic memories of the authors can be used as contextual keywords in query expressions to efficiently dig out the expected slides for reuse rather than using only the part-of-slide-descriptions-based keyword queries. As a system, a new slide repository is proposed, composed of slide material collections, slide content data and pieces of information from authors＇ episodic memories related to each slide and presentation together with a slide retrieval application enabling authors to use the episodic memories as part of queries. The result of our experiment shows that the episodic memory-used queries can give more discoverability than the keyword-based queries. Additionally, an improvement model is discussed on the slide retrieval for further slide-finding efficiency by expanding the episodic memories model in the repository taking in the links with the author-and-slide-related data and events having been post on the private and social media sites.
基金supported by the National Natural Science Foundation of China under Grant No.62172132.
文摘The surge of large-scale models in recent years has led to breakthroughs in numerous fields,but it has also introduced higher computational costs and more complex network architectures.These increasingly large and intricate networks pose challenges for deployment and execution while also exacerbating the issue of network over-parameterization.To address this issue,various network compression techniques have been developed,such as network pruning.A typical pruning algorithm follows a three-step pipeline involving training,pruning,and retraining.Existing methods often directly set the pruned filters to zero during retraining,significantly reducing the parameter space.However,this direct pruning strategy frequently results in irreversible information loss.In the early stages of training,a network still contains much uncertainty,and evaluating filter importance may not be sufficiently rigorous.To manage the pruning process effectively,this paper proposes a flexible neural network pruning algorithm based on the logistic growth differential equation,considering the characteristics of network training.Unlike other pruning algorithms that directly reduce filter weights,this algorithm introduces a three-stage adaptive weight decay strategy inspired by the logistic growth differential equation.It employs a gentle decay rate in the initial training stage,a rapid decay rate during the intermediate stage,and a slower decay rate in the network convergence stage.Additionally,the decay rate is adjusted adaptively based on the filter weights at each stage.By controlling the adaptive decay rate at each stage,the pruning of neural network filters can be effectively managed.In experiments conducted on the CIFAR-10 and ILSVRC-2012 datasets,the pruning of neural networks significantly reduces the floating-point operations while maintaining the same pruning rate.Specifically,when implementing a 30%pruning rate on the ResNet-110 network,the pruned neural network not only decreases floating-point operations by 40.8%but also enhances the classification accuracy by 0.49%compared to the original network.
基金the phased achievement of the major research project of the National Social Science Fund of China(Project Approval No.21VGQ010)supported by the 2021 Central University Basic Scientific Research Project of Lanzhou University(Project Approval No.21lzujbkyjd002).
文摘To cope with the challenges of CoViD-19,europe has adopted relevant measures of a data-based approach to governance,on which scholars have huge differences,and the related researches are conducive to further discussion on the differences.By sorting out the challenges posed by the pandemic to public security and data protection in europe,we can summarize the“european Solution”of the data-based approach to governance,including legislation,instruments,supervision,international cooperation,and continuity.The“Solution”has curbed the spread of the pandemic to a certain extent.However,due to the influence of the traditional values of the EU,the“Solution”is too idealistic in the balance between public security and data protection,which intensifies the dilemma and causes many problems,such as ambiguous legislation,inadequate effectiveness and security of instruments,an arduous endeavor in inter national cooperation,and imperfect regulations on digital green certificates.Therefore,in a major public health crisis,there is still a long way to go in exploring a balance between public security and data protection.
基金supported by the National Science and Technology Council,Taiwan under grants NSTC 111-2221-E-019-047 and NSTC 112-2221-E-019-030.
文摘In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenarios with non-Gaussian noise and heavy-tailed outliers.The proposed design modifies the extended Kalman filter(EKF)for the global navigation satellite system(GNSS),integrating the maximum correntropy criterion(MCC)and the variational Bayesian(VB)method.This adaptive algorithm effectively reduces non-line-of-sight(NLOS)reception contamination and improves estimation accuracy,particularly in time-varying GNSS measurements.Experimental results show that the proposed method significantly outperforms conventional approaches in estimation accuracy under heavy-tailed outliers and non-Gaussian noise.By combining MCC with VB approximation for real-time noise covariance estimation using fixed-point iteration,the VBMCEKF achieves superior filtering performance in challenging GNSS conditions.The method’s adaptability and precision make it ideal for improving satellite navigation performance in stochastic environments.
基金Project supported by the National Key Research and Development Program of China(2021YFB3500600,2021YFB3500605)Natural Science Foundation of Jiangsu Province(BK20220365)+5 种基金Key R&D Program of Jiangsu Province(BE2022142)Natural Science Foundation of the Jiangsu Higher Education Institutions of China(22KJB610002)Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX23_1419)Science and Technology Plan of Yangzhou(YZ2022030,YZ2023020)the State Key Laboratory of Clean and Efficient Coal-fired Power Generation and Pollution Control(D2022FK098)。
文摘The integration of surface filtration and catalytic decomposition functions in catalytic bags enables the synergistic removal of multiple pollutants(such as dust,nitrogen oxide,acid gases,and dioxins)in a single reactor,thus effectively reducing the cost and operational difficulties associated with flue gas treatment.In this study,Mn-Ce-Sm-Sn(MCSS)catalysts were prepared and loaded onto hightemperature resistant polyimide(P84)filter through ultrasonic impregnation to create composite catalytic filter.The results demonstrate that the NO conversion rates of the composite catalytic filter consistently achieve above 95%within the temperature range of 160-260℃,with a chlorobenzene T_(90)value of 230℃.The ultrasonic impregnation method effectively loaded the catalyst onto the filter,ensuring high dispersion both on the surface and inside the filter.This increased exposure of catalyst active sites enhances the catalytic activity of the composite catalytic filter.Additionally,increasing the catalyst loading leads to a gradual decrease in permeability,an increase in pressure drops and the long residence time of the flue gas,thereby improving catalytic activity.Compared to ordinary impregnation methods,ultrasonic impregnation improves the bonding strength between the catalyst and filter,as well as the permeability of the composite catalytic filter under the same loading conditions.Overall,this study presents a novel approach to prepare composite catalytic filter for the simultaneous removal of NO and chlorobenzene at low temperatures.
文摘A medical image encryption is proposed based on the Fisher-Yates scrambling,filter diffusion and S-box substitution.First,chaotic sequence associated with the plaintext is generated by logistic-sine-cosine system,which is used for the scrambling,substitution and diffusion processes.The three-dimensional Fisher-Yates scrambling,S-box substitution and diffusion are employed for the first round of encryption.The chaotic sequence is adopted for secondary encryption to scramble the ciphertext obtained in the first round.Then,three-dimensional filter is applied to diffusion for further useful information hiding.The key to the algorithm is generated by the combination of hash value of plaintext image and the input parameters.It improves resisting ability of plaintext attacks.The security analysis shows that the algorithm is effective and efficient.It can resist common attacks.In addition,the good diffusion effect shows that the scheme can solve the differential attacks encountered in the transmission of medical images and has positive implications for future research.
基金supported by the Key Research and Development Program of Ningxia(Grant No.2023BCF01046)。
文摘Brackish water(BW)irrigation may cause soil quality deterioration and thereby a decrease in crop yields.Here we examined the impacts of applying gasification filter cake(GFC),intercropping with Portulaca oleracea(PO),and their combination on soil quality,nutrient uptake by plants and tomato yields under BW irrigation.The treatments evaluated included(i)freshwater irrigation(Control),(ii)BW irrigation,(iii)GFC application under BW irrigation(BW+GFC),(iv)intercropping with PO under BW irrigation(BW+PO),and(v)the combined application of GFC and PO under BW irrigation(BW+PO+GFC).Overall,the use of BW for irrigation resulted in a decline in both soil quality(assessed by a soil quality index(SQI)integrating a wide range of key soil properties including salinity,nutrient availability and microbial activities)and crop yields.Nevertheless,when subjected to BW irrigation,the application of GFC successfully prevented soil salinity.Additionally,the intercropping of PO decreased the soil sodium adsorption ratio and improved the absorption of nutrients by plants.As a result,the BW+GFC+PO treatment generally showed higher tomato yield as compared to other BW-related treatments(i.e.BW,BW+GFC and BW+PO).Compared to BW,the BW+GFC+PO treatment had an average increase of 24.7% in the total fruit yield of four Cropping Seasons.Furthermore,the BW+GFC+PO treatment consistently exhibited the highest fruit quality index(FQI).Taken together,the combined application of GFC and PO is effective in promoting soil quality and crop yields under BW irrigation.
基金Supported by the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province(22KJB520012)the Research Project on Higher Education Reform in Jiangsu Province(2023JSJG781)the College Student Innovation and Entrepreneurship Training Program Project(202313571008Z)。
文摘Fault detection in industrial robot drive systems is a critical aspect of ensuring operational reliability and efficiency.To address the challenge of balancing accuracy and robustness in existing fault detection methods,this paper proposes an enhanced fault detection method based on the unscented Kalman filter(UKF).A comprehensive mathematical model of the brushless DC motor drive system is developed to provide a theoretical foundation for the design of subsequent fault detection methods.The conventional UKF estimation process is detailed,and its limitations in balancing estimation accuracy and robustness are addressed by introducing a dynamic,time-varying boundary layer.To further enhance detection performance,the method incorporates residual analysis using improved z-score and signal-tonoise ratio(SNR)metrics.Numerical simulations under both fault-free and faulty conditions demonstrate that the proposed approach achieves lower root mean square error(RMSE)in fault-free scenarios and provides reliable fault detection.These results highlight the potential of the proposed method to enhance the reliability and robustness of fault detection in industrial robot drive systems.
基金supported by the National Key R&D Program of China(No.2021YFB2011300)the Special Funds Project for the Transformation of Scientific and Technological Achievements of Jiangsu Province,China(No.BA2023039)+1 种基金the National Natural Science Foundation of China(No.52075262)the Fundamental Research Funds for the Central Universities,China(No.30922010706).
文摘The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this paper.First,a comprehensive nonlinear mathematical model that encompasses both matched and mismatched disturbances is formulated.Due to the fact that only position information can be measured,a linear Extended State Observer(ESO)is introduced to estimate unknown states and matched disturbances,while a dedicated disturbance observer is constructed to estimate mismatched disturbances.Different from the traditional observer results,the design of the disturbance observer used in this study is carried out under the constraint of output feedback.Furthermore,an output feedback nonlinear controller is proposed leveraging the aforementioned observers to achieve accurate trajectory tracking.To mitigate the inherent differential explosion problem of the traditional backstepping framework,a finite-time stable command filter is incorporated.Simultaneously,considering transient filtering errors,a set of error compensation signals are designed to counter their negative impact effectively.Theoretical analysis affirms that the proposed control strategy ensures the boundedness of all signals within the closed-loop system.Additionally,under the specific condition of only time-invariant disturbances in the system,the conclusion of asymptotic stability is established.Finally,the algorithm’s efficacy is validated through comparative experiments.
文摘Terrain Aided Navigation(TAN)technology has become increasingly important due to its effectiveness in environments where Global Positioning System(GPS)is unavailable.In recent years,TAN systems have been extensively researched for both aerial and underwater navigation applications.However,many TAN systems that rely on recursive Unmanned Aerial Vehicle(UAV)position estimation methods,such as Extended Kalman Filters(EKF),often face challenges with divergence and instability,particularly in highly non-linear systems.To address these issues,this paper proposes and investigates a hybrid two-stage TAN positioning system for UAVs that utilizes Particle Filter.To enhance the system’s robustness against uncertainties caused by noise and to estimate additional system states,a Fuzzy Particle Filter(FPF)is employed in the first stage.This approach introduces a novel terrain composite feature that enables a fuzzy expert system to analyze terrain non-linearities and dynamically adjust the number of particles in real-time.This design allows the UAV to be efficiently localized in GPS-denied environments while also reducing the computational complexity of the particle filter in real-time applications.In the second stage,an Error State Kalman Filter(ESKF)is implemented to estimate the UAV’s altitude.The ESKF is chosen over the conventional EKF method because it is more suitable for non-linear systems.Simulation results demonstrate that the proposed fuzzy-based terrain composite method achieves high positional accuracy while reducing computational time and memory usage.
基金supported in part by the National Natural Science Foundation of China(12171124,61933007)the Natural Science Foundation of Heilongjiang Province of China(ZD2022F003)+2 种基金the National High-End Foreign Experts Recruitment Plan of China(G2023012004L)the Royal Society of UKthe Alexander von Humboldt Foundation of Germany
文摘In this paper, the problem of cubature Kalman fusion filtering(CKFF) is addressed for multi-sensor systems under amplify-and-forward(AaF) relays. For the purpose of facilitating data transmission, AaF relays are utilized to regulate signal communication between sensors and filters. Here, the randomly varying channel parameters are represented by a set of stochastic variables whose occurring probabilities are permitted to exhibit bounded uncertainty. Employing the spherical-radial cubature principle, a local filter under AaF relays is initially constructed. This construction ensures and minimizes an upper bound of the filtering error covariance by designing an appropriate filter gain. Subsequently, the local filters are fused through the application of the covariance intersection fusion rule. Furthermore, the uniform boundedness of the filtering error covariance's upper bound is investigated through establishing certain sufficient conditions. The effectiveness of the proposed CKFF scheme is ultimately validated via a simulation experiment concentrating on a three-phase induction machine.
基金Supported by the Fundamental Research Funds for the Central Universities(ZYGX2021J008)。
文摘A novel substrate integrated microstrip to ultra-thin cavity filter transition operating in the W-band is proposed in this letter.The structure is a new method of connecting microstrip circuits and waveguide filters,and this new structure enables a planar integrated transition from microstrip lines to ultra-thin cavity filters,thereby reducing the size of the transition structure and achieving miniaturization.The structure includes a conventional tapered microstrip transition structure,which guides the electromagnetic field from the microstrip line to the reduced-height dielectric-filled waveguide,and an air-filled matching cavity which is placed between the dielectric-filled waveguide and the ultra-thin cavity filter.The heights of the microstrip line,the dielectric-filled waveguide and the ultra-thin cavity filter are the same,enabling seamless integration within a planar radio-frequency(RF)circuit.To facilitate testing,mature finline transition structures are integrated at both ends of the microstrip line during fabrications.The simulation results of the fabricated microstrip to ultra-thin cavity filter transition with the finline transition structure,with a passband of 91.5-96.5 GHz,has an insertion loss of less than 1.9 dB and a return loss lower than-20 dB.And the whole structure has also been measured which achieves an insertion loss less than 2.6 dB and a return loss lower than-15 dB within the filter's passband,including the additional insertion loss introduced by the finline transitions.Finally,a W-band compact up-conversion module is designed,and the test results show that after using the proposed structure,the module achieves 95 dBc suppression of the 84 GHz local oscillator.It is also demonstrated that the structure proposed in this letter achieves miniaturization of the system integration without compromising the filter performance.
文摘Filter capacitors play an important role in altern-ating current(AC)-line filtering for stabilizing voltage,sup-pressing harmonics,and improving power quality.However,traditional aluminum electrolytic capacitors(AECs)suffer from a large size,short lifespan,low power density,and poor reliability,which limits their use.In contrast,ultrafast supercapacitors(SCs)are ideal for replacing commercial AECs because of their extremely high power densities,fast charging and discharging,and excellent high-frequency re-sponse.We review the design principles and key parameters for ultrafast supercapacitors and summarize research pro-gress in recent years from the aspects of electrode materials,electrolytes,and device configurations.The preparation,structures,and frequency response performance of electrode materials mainly consisting of carbon materials such as graphene and carbon nanotubes,conductive polymers,and transition metal compounds,are focused on.Finally,future research directions for ultrafast SCs are suggested.
基金supported in part by the National Natural Science Foundation of China(61873348,6230 3266,62273200)JSPS(Japan Society for the Promotion of Science) KAKENHI(22H03998,23K25252)
文摘Dear Editor,This letter presents an improved repetitive controller(IRC) that uses a complex-coefficient filter to enhance the tracking performance of a system for periodic signals. Compared with the low-pass filter used in the conventional repetitive controller(CRC), the complex-coefficient filter causes less change in the phase and amplitude of a signal at the frequencies of the periodic signal, especially at the fundamental frequency, when the two filters have the same cutofffrequency.
