Filtering is a recursive estimation of hidden states of a dynamic system from noisy measurements.Such problems appear in several branches of science and technology,ranging from target tracking to biomedical monitoring...Filtering is a recursive estimation of hidden states of a dynamic system from noisy measurements.Such problems appear in several branches of science and technology,ranging from target tracking to biomedical monitoring.A commonly practiced approach of filtering with nonlinear systems is Gaussian filtering.The early Gaussian filters used a derivative-based implementation,and suffered from several drawbacks,such as the smoothness requirements of system models and poor stability.A derivative-free numerical approximation-based Gaussian filter,named the unscented Kalman filter(UKF),was introduced in the nineties,which offered several advantages over the derivativebased Gaussian filters.Since the proposition of UKF,derivativefree Gaussian filtering has been a highly active research area.This paper reviews significant developments made under Gaussian filtering since the proposition of UKF.The review is particularly focused on three categories of developments:i)advancing the numerical approximation methods;ii)modifying the conventional Gaussian approach to further improve the filtering performance;and iii)constrained filtering to address the problem of discrete-time formulation of process dynamics.This review highlights the computational aspect of recent developments in all three categories.The performance of various filters are analyzed by simulating them with real-life target tracking problems.展开更多
High-selectivity common-mode(CM)and differential-mode(DM)reflectionless balanced bandpass filters(BBPFs)are proposed in this article.By loading absorption networks at single/both ends of the basic ring resonator,input...High-selectivity common-mode(CM)and differential-mode(DM)reflectionless balanced bandpass filters(BBPFs)are proposed in this article.By loading absorption networks at single/both ends of the basic ring resonator,input-/two-port wideband CM and DM reflectionless performance,wideband filtering performance and all-stop CM suppression are obtained.The absorption network composed of K-sections of coupled-lines(CLs)terminated with grounded resistors can not only extend the filtering performance to high order,but also realize wideband absorption of CM noise and out-of-band DM signals.Absorptive stubs are loaded at ports to increase the design flexibility and enhance the absorption.As for the input-reflectionless type,multiple independently controlled transmission zeros(TZs)are obtained by the TZ control network to improves the selectivity and out-of-band rejection.A set of 2 GHz micro-strip BBPFs are designed and measured,which shows simultaneous CM and DM absorption performance.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
With the rapid development of wireless techniques,the bandpass filter(BPF)is required to cover microwave and millimeter-wave frequency bands simultaneously with good mid-band suppression.However,it is difficult to imp...With the rapid development of wireless techniques,the bandpass filter(BPF)is required to cover microwave and millimeter-wave frequency bands simultaneously with good mid-band suppression.However,it is difficult to implement such BPF due to the large frequency ratio and wideband rejection.This paper presents a superior method to realize a dual-band BPF with a large frequency ratio maintaining compact size and low design complexity.This is contributed by an ultra-wide stopband BPF with inherent discriminating excited degree at spurious frequencies.By properly arranging the feeding position and electrical length ratio of stepped impedance resonator(SIR),the excited degree at specific spurious frequencies can be flexibly adjusted to achieve desired suppression level without affecting characteristics at the fundamental passband.For validation,two BPFs were simulated,fabricated and measured,exhibiting suppression levels of 20.3 dB and 35 dB up to 18f0 and 10.53f0 respectively.Based on this,a dual-band BPF with a large frequency ratio can be easily constructed.For demonstration,a dual-band BPF operating at 3.55 GHz and 43.15 GHz is implemented.A frequency ratio up to 12.15 and mid-band suppression level better than 28 dB had been achieved.Advantages of compactness,simplicity and excellent performance of the proposed work can be observed.展开更多
Power transformers are vital components in electric grids;however,methods to optimise their loading to extend lifespan while accounting for insulation degradation remain underdeveloped.This research paper introduces a...Power transformers are vital components in electric grids;however,methods to optimise their loading to extend lifespan while accounting for insulation degradation remain underdeveloped.This research paper introduces a novel integrated data-driven framework that combines particle filtering and model predictive health(PF-MPH)model for the predictive health manage-ment of power transformers.Initially,the particle filter probabilistically estimates power transformers'remaining life(R_(L))using direct winding hotspot temperature(χ_(H))measurements.The obtained R_(L)will then be used to calculate the degree of poly-merisation(DP)level and assess the current insulation condition.After that,a comparative analysis between direct and model-basedχ_(H)measurement methods is performed to highlight the superior accuracy of direct measurements for predictive health management.Then,the MPH optimisation algorithm,which uses the R_(L)and DP forecasts from the PF method,derives an optimal trajectory over the transformer's R_(L)that balances the costs of increased loading against the benefits gained from prolonged insulation longevity.The findings show that the proposed PF-MPH model has successfully reduced the χ_(H)by 2.46%over the predicted 19 years.This approach is expected to enable grid operators to optimise transformer loading schedules to extend the R_(L)of these critical assets in a cost-effective manner.展开更多
Pure magnesia filter and periclase-spinel filter were prepared using porous MgO powder and Al2O3 micro-powder as raw materials.The filtration efficiency and purification mechanism of the two sets of filters on molten ...Pure magnesia filter and periclase-spinel filter were prepared using porous MgO powder and Al2O3 micro-powder as raw materials.The filtration efficiency and purification mechanism of the two sets of filters on molten steel were investigated through steel casting tests.The results show that on the basis of surviving the thermal shock of molten steel,both filters can significantly reduce the number of non-metallic inclusions and total oxygen content of steel,thereby improving the cleanliness of the molten steel.After the thermal shock of molten steel,cracks were found in the microstructure of pure magnesia filter.Via the diffusion of non-metallic inclusions from steel into MgO grains of the filter to form solid solution,the inclusions were adsorbed to the internal and external surfaces of the pure magnesia filter.The number of inclusions was reduced by 62.5%,and the total oxygen content decreased from 0.892 to 0.265 wt.%after filtration,achieving a filtration efficiency of 70.3%.Compared with the pure magnesia filter,no cracks were found in the microstructure of the periclase-spinel filter.The mass transfer rate was accelerated due to the diffusion of inclusions from steel into MgO and MgAl2O4 grains of the filter,as well as the higher high-temperature liquid content and smaller pore structure of the filter.More non-metallic inclusions were able to enter the interior of the filter,which made the periclase-spinel filter more capable of adsorbing inclusions from steel and reducing total oxygen content.The periclase-spinel filter reduced the number of inclusions in steel by 84.4%and decreased the total oxygen content of the steel from 0.892 to 0.119 wt.%,with a filtration efficiency of 86.7%,demonstrating excellent comprehensive performance.展开更多
This work proposes a novel design for a narrowband filter operating in the mid-wave infrared(MWIR)spectrum.The filter is designed with a single layer of slab waveguide decorated with a layer of gold grating arrays.Thi...This work proposes a novel design for a narrowband filter operating in the mid-wave infrared(MWIR)spectrum.The filter is designed with a single layer of slab waveguide decorated with a layer of gold grating arrays.This design demonstrates superior narrowband transmission properties within the MWIR range,which can be explained in the framework of guided-mode resonance(GMR).Since MWIR spectral data is crucial for identifying the chemical fingerprint of man-made objects and natural materials,the GMR filters hold great potential in integration with commercial MWIR photodetectors and focal plane arrays(FPAs)and addressing the market’s demand for ultra-compact spectral detection solutions.Theoretical studies have investigated the influential parameters in the GMR filter design and provided the methods towards optimal filtering performance.The center wavelength of these transmission filters exhibits significant tunability,spanning from 3μm to 5μm across the MWIR spectrum,while the full width at half maximum(FWHM)exhibits remarkable variability,ranging from 5.7 nm to 101.0 nm,enabling the attainment of desired filter performance contingent upon judicious waveguide material selection and optimized structural design.This work forges a path toward integrating multifunctional capabilities into ultra-compact MWIR sensors.展开更多
In-loop filters have been comprehensively explored during the development of video coding standards due to their remarkable noise-reduction capabilities.In the early stage of video coding,in-loop filters,such as the d...In-loop filters have been comprehensively explored during the development of video coding standards due to their remarkable noise-reduction capabilities.In the early stage of video coding,in-loop filters,such as the deblocking filter,sample adaptive offset,and adaptive loop filter,were performed separately for each component.Recently,cross-component filters have been studied to improve chroma fidelity by exploiting correlations between the luma and chroma channels.This paper introduces the cross-component filters used in the state-ofthe-art video coding standards,including the cross-component adaptive loop filter and cross-component sample adaptive offset.Crosscomponent filters aim to reduce compression artifacts based on the correlation between different components and provide more accurate pixel reconstruction values.We present their origin,development,and status in the current video coding standards.Finally,we conduct discussions on the further evolution of cross-component filters.展开更多
This paper demonstrated the generation of multi-wavelength bound state noise-like pulse(BNLP)in a dispersion-managed composite-filtered fiber laser consisting of nonlinear polarization rotation(NPR)and loop.In the cas...This paper demonstrated the generation of multi-wavelength bound state noise-like pulse(BNLP)in a dispersion-managed composite-filtered fiber laser consisting of nonlinear polarization rotation(NPR)and loop.In the case of BNLP,the generation is caused by the interaction between two noise-like pulses(NLPs)induced by the comb-filtering effect,and bound state level can be artificially controlled in the researches.Our work provides a new method for generating low-coherence pulses and establishes a research idea for the study of the comb-filtering effects.展开更多
In this paper,the newly-derived maximum correntropy Kalman filter(MCKF)is re-derived from the M-estimation perspective,where the MCKF can be viewed as a special case of the M-estimations and the Gaussian kernel functi...In this paper,the newly-derived maximum correntropy Kalman filter(MCKF)is re-derived from the M-estimation perspective,where the MCKF can be viewed as a special case of the M-estimations and the Gaussian kernel function is a special case of many robust cost functions.Based on the derivation process,a unified form for the robust Gaussian filters(RGF)based on M-estimation is proposed to suppress the outliers and non-Gaussian noise in the measurement.The RGF provides a unified form for one Gaussian filter with different cost functions and a unified form for one robust filter with different approximating methods for the involved Gaussian integrals.Simulation results show that RGF with different weighting functions and different Gaussian integral approximation methods has robust antijamming performance.展开更多
Active damping(AD)strategy is an economical and efficient method to solve the resonant problem of the permanent magnet synchronous motor(PMSM)drive system with inductor-capacitor(LC)sine wave filter.In this article,th...Active damping(AD)strategy is an economical and efficient method to solve the resonant problem of the permanent magnet synchronous motor(PMSM)drive system with inductor-capacitor(LC)sine wave filter.In this article,the AD methods used in PMSM drive system are classified as inherent damping(ID),state variable feedback,and digital filter.Based on this,the purpose of this article is to provide an overview and analysis of the AD methods on PMSM drive system in recent years,and to comprehensively review,compare,and summarize the stability,dynamic performance,robustness,and algorithm complexity.Furthermore,a new expansion of AD method based on capacitor current feedback with high-pass filter(HPF-CCF)is studied to ensure the effectiveness when the resonant frequency is around sixth of the sampling frequency.The simulation and experimental results validate the effectiveness of theoretical analysis.展开更多
In order to detect the deformation in real-time of the GPS time series and improve its reliability, the multiple Kalman filters model with shaping filter was proposed. Two problems were solved: firstly, because the GP...In order to detect the deformation in real-time of the GPS time series and improve its reliability, the multiple Kalman filters model with shaping filter was proposed. Two problems were solved: firstly, because the GPS real-time deformation series with a high sampling rate contain coloured noise, the multiple Kalman filter model requires the white noise, and the multiple Kalman filters model is augmented by a shaping filter in order to reduce the colored noise; secondly, the multiple Kalman filters model with shaping filter can detect the deformation epoch in real-time and improve the quality of GPS measurements for the real-time deformation applications. Based on the comparisons of the applications in different GPS time series with different models, the advantages of the proposed model were illustrated. The proposed model can reduce the colored noise, detect the smaller changes, and improve the precision of the detected deformation epoch.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
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
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
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
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Filtering is a recursive estimation of hidden states of a dynamic system from noisy measurements.Such problems appear in several branches of science and technology,ranging from target tracking to biomedical monitoring.A commonly practiced approach of filtering with nonlinear systems is Gaussian filtering.The early Gaussian filters used a derivative-based implementation,and suffered from several drawbacks,such as the smoothness requirements of system models and poor stability.A derivative-free numerical approximation-based Gaussian filter,named the unscented Kalman filter(UKF),was introduced in the nineties,which offered several advantages over the derivativebased Gaussian filters.Since the proposition of UKF,derivativefree Gaussian filtering has been a highly active research area.This paper reviews significant developments made under Gaussian filtering since the proposition of UKF.The review is particularly focused on three categories of developments:i)advancing the numerical approximation methods;ii)modifying the conventional Gaussian approach to further improve the filtering performance;and iii)constrained filtering to address the problem of discrete-time formulation of process dynamics.This review highlights the computational aspect of recent developments in all three categories.The performance of various filters are analyzed by simulating them with real-life target tracking problems.
文摘High-selectivity common-mode(CM)and differential-mode(DM)reflectionless balanced bandpass filters(BBPFs)are proposed in this article.By loading absorption networks at single/both ends of the basic ring resonator,input-/two-port wideband CM and DM reflectionless performance,wideband filtering performance and all-stop CM suppression are obtained.The absorption network composed of K-sections of coupled-lines(CLs)terminated with grounded resistors can not only extend the filtering performance to high order,but also realize wideband absorption of CM noise and out-of-band DM signals.Absorptive stubs are loaded at ports to increase the design flexibility and enhance the absorption.As for the input-reflectionless type,multiple independently controlled transmission zeros(TZs)are obtained by the TZ control network to improves the selectivity and out-of-band rejection.A set of 2 GHz micro-strip BBPFs are designed and measured,which shows simultaneous CM and DM absorption performance.
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supported by the National Natural Science Foundation of China(No.61671485).
文摘With the rapid development of wireless techniques,the bandpass filter(BPF)is required to cover microwave and millimeter-wave frequency bands simultaneously with good mid-band suppression.However,it is difficult to implement such BPF due to the large frequency ratio and wideband rejection.This paper presents a superior method to realize a dual-band BPF with a large frequency ratio maintaining compact size and low design complexity.This is contributed by an ultra-wide stopband BPF with inherent discriminating excited degree at spurious frequencies.By properly arranging the feeding position and electrical length ratio of stepped impedance resonator(SIR),the excited degree at specific spurious frequencies can be flexibly adjusted to achieve desired suppression level without affecting characteristics at the fundamental passband.For validation,two BPFs were simulated,fabricated and measured,exhibiting suppression levels of 20.3 dB and 35 dB up to 18f0 and 10.53f0 respectively.Based on this,a dual-band BPF with a large frequency ratio can be easily constructed.For demonstration,a dual-band BPF operating at 3.55 GHz and 43.15 GHz is implemented.A frequency ratio up to 12.15 and mid-band suppression level better than 28 dB had been achieved.Advantages of compactness,simplicity and excellent performance of the proposed work can be observed.
基金supported by Shandong Provincial Natural Science Foundation(ZR2024ME229,ZR2024ZD29).
文摘Power transformers are vital components in electric grids;however,methods to optimise their loading to extend lifespan while accounting for insulation degradation remain underdeveloped.This research paper introduces a novel integrated data-driven framework that combines particle filtering and model predictive health(PF-MPH)model for the predictive health manage-ment of power transformers.Initially,the particle filter probabilistically estimates power transformers'remaining life(R_(L))using direct winding hotspot temperature(χ_(H))measurements.The obtained R_(L)will then be used to calculate the degree of poly-merisation(DP)level and assess the current insulation condition.After that,a comparative analysis between direct and model-basedχ_(H)measurement methods is performed to highlight the superior accuracy of direct measurements for predictive health management.Then,the MPH optimisation algorithm,which uses the R_(L)and DP forecasts from the PF method,derives an optimal trajectory over the transformer's R_(L)that balances the costs of increased loading against the benefits gained from prolonged insulation longevity.The findings show that the proposed PF-MPH model has successfully reduced the χ_(H)by 2.46%over the predicted 19 years.This approach is expected to enable grid operators to optimise transformer loading schedules to extend the R_(L)of these critical assets in a cost-effective manner.
基金supported by the Key Project of the National Natural Science Foundation of China(Grant No.U21A2058 and U1860205)the Natural Science Funds of Hubei Province for Distinguished Young Scholars(Grant No.2020CFA088).
文摘Pure magnesia filter and periclase-spinel filter were prepared using porous MgO powder and Al2O3 micro-powder as raw materials.The filtration efficiency and purification mechanism of the two sets of filters on molten steel were investigated through steel casting tests.The results show that on the basis of surviving the thermal shock of molten steel,both filters can significantly reduce the number of non-metallic inclusions and total oxygen content of steel,thereby improving the cleanliness of the molten steel.After the thermal shock of molten steel,cracks were found in the microstructure of pure magnesia filter.Via the diffusion of non-metallic inclusions from steel into MgO grains of the filter to form solid solution,the inclusions were adsorbed to the internal and external surfaces of the pure magnesia filter.The number of inclusions was reduced by 62.5%,and the total oxygen content decreased from 0.892 to 0.265 wt.%after filtration,achieving a filtration efficiency of 70.3%.Compared with the pure magnesia filter,no cracks were found in the microstructure of the periclase-spinel filter.The mass transfer rate was accelerated due to the diffusion of inclusions from steel into MgO and MgAl2O4 grains of the filter,as well as the higher high-temperature liquid content and smaller pore structure of the filter.More non-metallic inclusions were able to enter the interior of the filter,which made the periclase-spinel filter more capable of adsorbing inclusions from steel and reducing total oxygen content.The periclase-spinel filter reduced the number of inclusions in steel by 84.4%and decreased the total oxygen content of the steel from 0.892 to 0.119 wt.%,with a filtration efficiency of 86.7%,demonstrating excellent comprehensive performance.
基金supported by the National Key Research and Development Program of China under Grant No.2019YFB2203400the National Natural Science Foundation of China under Grant No.61974014.
文摘This work proposes a novel design for a narrowband filter operating in the mid-wave infrared(MWIR)spectrum.The filter is designed with a single layer of slab waveguide decorated with a layer of gold grating arrays.This design demonstrates superior narrowband transmission properties within the MWIR range,which can be explained in the framework of guided-mode resonance(GMR).Since MWIR spectral data is crucial for identifying the chemical fingerprint of man-made objects and natural materials,the GMR filters hold great potential in integration with commercial MWIR photodetectors and focal plane arrays(FPAs)and addressing the market’s demand for ultra-compact spectral detection solutions.Theoretical studies have investigated the influential parameters in the GMR filter design and provided the methods towards optimal filtering performance.The center wavelength of these transmission filters exhibits significant tunability,spanning from 3μm to 5μm across the MWIR spectrum,while the full width at half maximum(FWHM)exhibits remarkable variability,ranging from 5.7 nm to 101.0 nm,enabling the attainment of desired filter performance contingent upon judicious waveguide material selection and optimized structural design.This work forges a path toward integrating multifunctional capabilities into ultra-compact MWIR sensors.
基金supported in part by National Science Foundation of China under Grant No.62031013PCL-CMCC Foundation for Science and Innovation under Grant No.2024ZY1C0040+1 种基金New Cornerstone Science Foundation for the Xplorer PrizeHigh performance Computing Platform of Peking University。
文摘In-loop filters have been comprehensively explored during the development of video coding standards due to their remarkable noise-reduction capabilities.In the early stage of video coding,in-loop filters,such as the deblocking filter,sample adaptive offset,and adaptive loop filter,were performed separately for each component.Recently,cross-component filters have been studied to improve chroma fidelity by exploiting correlations between the luma and chroma channels.This paper introduces the cross-component filters used in the state-ofthe-art video coding standards,including the cross-component adaptive loop filter and cross-component sample adaptive offset.Crosscomponent filters aim to reduce compression artifacts based on the correlation between different components and provide more accurate pixel reconstruction values.We present their origin,development,and status in the current video coding standards.Finally,we conduct discussions on the further evolution of cross-component filters.
基金supported by the Research Fund of Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology(No.2020B1212030010)。
文摘This paper demonstrated the generation of multi-wavelength bound state noise-like pulse(BNLP)in a dispersion-managed composite-filtered fiber laser consisting of nonlinear polarization rotation(NPR)and loop.In the case of BNLP,the generation is caused by the interaction between two noise-like pulses(NLPs)induced by the comb-filtering effect,and bound state level can be artificially controlled in the researches.Our work provides a new method for generating low-coherence pulses and establishes a research idea for the study of the comb-filtering effects.
基金supported by the Basic Science Center Program of the National Natural Science Foundation of China(62388101)the National Natural Science Foundation of China(61873275).
文摘In this paper,the newly-derived maximum correntropy Kalman filter(MCKF)is re-derived from the M-estimation perspective,where the MCKF can be viewed as a special case of the M-estimations and the Gaussian kernel function is a special case of many robust cost functions.Based on the derivation process,a unified form for the robust Gaussian filters(RGF)based on M-estimation is proposed to suppress the outliers and non-Gaussian noise in the measurement.The RGF provides a unified form for one Gaussian filter with different cost functions and a unified form for one robust filter with different approximating methods for the involved Gaussian integrals.Simulation results show that RGF with different weighting functions and different Gaussian integral approximation methods has robust antijamming performance.
基金supported in part by the National Natural Science Foundational of China under Grants 62373363 and 52007190
文摘Active damping(AD)strategy is an economical and efficient method to solve the resonant problem of the permanent magnet synchronous motor(PMSM)drive system with inductor-capacitor(LC)sine wave filter.In this article,the AD methods used in PMSM drive system are classified as inherent damping(ID),state variable feedback,and digital filter.Based on this,the purpose of this article is to provide an overview and analysis of the AD methods on PMSM drive system in recent years,and to comprehensively review,compare,and summarize the stability,dynamic performance,robustness,and algorithm complexity.Furthermore,a new expansion of AD method based on capacitor current feedback with high-pass filter(HPF-CCF)is studied to ensure the effectiveness when the resonant frequency is around sixth of the sampling frequency.The simulation and experimental results validate the effectiveness of theoretical analysis.
基金Project(20120022120011)supported by the Specialized Research Fund for the Doctoral Program of Higher Education of ChinaProject(2652012062)supported by the Fundamental Research Funds for the Central Universities,China
文摘In order to detect the deformation in real-time of the GPS time series and improve its reliability, the multiple Kalman filters model with shaping filter was proposed. Two problems were solved: firstly, because the GPS real-time deformation series with a high sampling rate contain coloured noise, the multiple Kalman filter model requires the white noise, and the multiple Kalman filters model is augmented by a shaping filter in order to reduce the colored noise; secondly, the multiple Kalman filters model with shaping filter can detect the deformation epoch in real-time and improve the quality of GPS measurements for the real-time deformation applications. Based on the comparisons of the applications in different GPS time series with different models, the advantages of the proposed model were illustrated. The proposed model can reduce the colored noise, detect the smaller changes, and improve the precision of the detected deformation epoch.
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.
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 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.
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(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.
