The robust H∞ filtering problem for uncertain discrete-time Markovian jump linear systems with mode- dependent time-delays is investigated. Attention is focused on designing a Markovian jump linear filter that ensure...The robust H∞ filtering problem for uncertain discrete-time Markovian jump linear systems with mode- dependent time-delays is investigated. Attention is focused on designing a Markovian jump linear filter that ensures robust stochastic stability while achieving a prescribed H∞ performance level of the resulting filtering error system, for all admissible uncertainties. The key features of the approach include the introduction of a new type of stochastic Lyapunov functional and some free weighting matrix variables. Sufficient conditions for the solvability of this problem are obtained in terms of a set of linear matrix inequalities. Numerical examples are provided to demonstrate the reduced conservatism of the proposed approach.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
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
A novel H∞ design methodology for a neural network-based nonlinear filtering scheme is addressed. Firstly, neural networks are employed to approximate the nonlinearities. Next, the nonlinear dynamic system is represe...A novel H∞ design methodology for a neural network-based nonlinear filtering scheme is addressed. Firstly, neural networks are employed to approximate the nonlinearities. Next, the nonlinear dynamic system is represented by the mode-dependent linear difference inclusion （LDI）. Finally, based on the LDI model, a neural network-based nonlinear filter （NNBNF） is developed to minimize the upper bound of H∞ gain index of the estimation error under some linear matrix inequality （LMI） constraints. Compared with the existing nonlinear filters, NNBNF is time-invariant and numerically tractable. The validity and applicability of the proposed approach are successfully demonstrated in an illustrative example.展开更多
Robust H-infinity filtering for a class of uncertain discrete-time linear systems with time delays and missing measurements is studied in this paper. The uncertain parameters are supposed to reside in a convex polytop...Robust H-infinity filtering for a class of uncertain discrete-time linear systems with time delays and missing measurements is studied in this paper. The uncertain parameters are supposed to reside in a convex polytope and the missing measurements are described by a binary switching sequence satisfying a Bernoulli distribution. Our attention is focused on the analysis and design of robust H-infinity filters such that, for all admissible parameter uncertainties and all possible missing measurements, the filtering error system is exponentially mean-square stable with a prescribed H-infinity disturbance attenuation level. A parameter-dependent approach is proposed to derive a less conservative result. Sufficient conditions are established for the existence of the desired filter in terms of certain linear matrix inequalities （LMIs）. When these LMIs are feasible, an explicit expression of the desired filter is also provided. Finally, a numerical example is presented to illustrate the effectiveness and applicability of the proposed method.展开更多
To obtain a stable and proper linear filter to make the filtering error system robustly and strictly passive, the problem of full-order robust passive filtering for continuous-time polytopic uncertain time-delay syste...To obtain a stable and proper linear filter to make the filtering error system robustly and strictly passive, the problem of full-order robust passive filtering for continuous-time polytopic uncertain time-delay systems was investigated. A criterion for the passivity of time-delay systems was firstly provided in terms of linear matrix inequalities (LMI). Then an LMI sufficient condition for the existence of a robust filter was established and a design procedure was proposed for this type of systems. A numerical example demonstrated the feasibility of the filtering design procedure.展开更多
The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions a...The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions and are easy to lose detailed information.So we propose a rendered image denoising method with filtering guided by lighting information.First,we design an image segmentation algorithm based on lighting information to segment the image into different illumination areas.Then,we establish the parameter prediction model guided by lighting information for filtering(PGLF)to predict the filtering parameters of different illumination areas.For different illumination areas,we use these filtering parameters to construct area filters,and the filters are guided by the lighting information to perform sub-area filtering.Finally,the filtering results are fused with auxiliary features to output denoised images for improving the overall denoising effect of the image.Under the physically based rendering tool(PBRT)scene and Tungsten dataset,the experimental results show that compared with other guided filtering denoising methods,our method improves the peak signal-to-noise ratio(PSNR)metrics by 4.2164 dB on average and the structural similarity index(SSIM)metrics by 7.8%on average.This shows that our method can better reduce the noise in complex lighting scenesand improvethe imagequality.展开更多
The problem of robust H∞ filtering for a class of neutral jump systems with time-delay and norm- bounded uncertainties is considered. By re-constructing the system, the dynamics of overall augmented error systems is ...The problem of robust H∞ filtering for a class of neutral jump systems with time-delay and norm- bounded uncertainties is considered. By re-constructing the system, the dynamics of overall augmented error systems is obtained which involves unknown inputs represented by disturbances, model uncertainties and time-delays. As to the nominal system, sufficient conditions are provided for the existence of the mode-dependent H∞ filter by selecting the appropriate Lyapunov-Krasovskii function and the robust H∞ filter is proposed for the jump system while considering the time-delays and uncertainties. Both of above conditions for the existence of the H∞ filter and roust H∞ filter are presented in terms of linear matrix inequalities, and convex optimization problems are formulated to design the desired filters. By employing the proposed mode-dependent H∞ filter, the systems have the stochastic stability and better ability of restraining disturbances stochastically, and the given prescribed H∞ performance is guaranteed. Simulation resuhs illustrate the effectiveness of developed techniques.展开更多
Although guided image filtering(GIF) is known for preserving edges and fast computation,it may produce inaccurate outputs in depth map restoration.In this paper,a novel confidence-weighted GIF called mutual-structure ...Although guided image filtering(GIF) is known for preserving edges and fast computation,it may produce inaccurate outputs in depth map restoration.In this paper,a novel confidence-weighted GIF called mutual-structure weighted GIF(MSWGIF) is proposed,which replaces the mean filtering strategy in GIF during handling overlapping windows.The confidence value is composed of a depth term and a mutual-structure term,where the depth term is utilized to protect the edges of the output,and the mutual-structure term helps to select accurate windows during the structure characteristics of the guidance image are transferred to the output.Experimental results show that MSWGIF reduces the root mean square error(RMSE) by an average of 12.37%,and the average growth rate of correlation(CORR) is 0.07% on average.Additionally,the average growth rate of structure similarity index measure(SSIM) is 0.34%.展开更多
This paper focuses on the problem of dissipative filtering for linear continuous-time polytopic uncertain time-delay systems. To obtain a stable and proper linear filter such that the filtering error system is strictl...This paper focuses on the problem of dissipative filtering for linear continuous-time polytopic uncertain time-delay systems. To obtain a stable and proper linear filter such that the filtering error system is strictly dissipative for all admissible uncertainties,a new dissipativity criterion which realizes separation between the Lyapunov matrices and the system dynamic matrices is firstly provided in terms of linear matrix inequalities ( LMI) . Then an LMI sufficient condition for the existence of a robust filter is established and a design procedure is proposed for this type of systems. One numerical example demonstrates less conservativeness of the proposed criterion,the other numerical example illustrates the validity of the proposed filter design.展开更多
This study introduces an advanced recommender system for technology enhanced learning(TEL)that synergizes neural collaborative filtering,sentiment analysis,and an adaptive learning rate to address the limitations of t...This study introduces an advanced recommender system for technology enhanced learning(TEL)that synergizes neural collaborative filtering,sentiment analysis,and an adaptive learning rate to address the limitations of traditional TEL systems.Recognizing the critical gap in existing approaches—primarily their neglect of user emotional feedback and static learning paths—our model innovatively incorporates sentiment analysis to capture and respond to nuanced emotional feedback from users.Utilizing bidirectional encoder representations from Transformers for sentiment analysis,our system not only understands but also respects user privacy by processing feedback without revealing sensitive information.The adaptive learning rate,inspired by AdaGrad,allows our model to adjust its learning trajectory based on the sentiment scores associated with user feedback,ensuring a dynamic response to both positive and negative sentiments.This dual approach enhances the system’s adapt-ability to changing user preferences and improves its contentment understanding.Our methodology involves a comprehensive analysis of both the content of learning materials and the behaviors and preferences of learners,facilitating a more personalized learning experience.By dynamically adjusting recommendations based on real-time user data and behavioral analysis,our system leverages the collective insights of similar users and rele-vant content.We validated our approach against three datasets-MovieLens,Amazon,and a proprietary TEL dataset—and saw significant improvements in recommendation precision,F-score,and mean absolute error.The results indicate the potential of integrating sentiment analysis and adaptive learning rates into TEL recommender systems,marking a step forward in developing more responsive and user-centric educational technologies.This study paves the way for future advancements in TEL systems,emphasizing the importance of emotional intelli-gence and adaptability in enhancing the learning experience.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
Cultural filtering is deeply embedded in cross-cultural literary exchange and exerts a lasting influence on both the transmission and interpretation of literary works.This article examines the English translation of B...Cultural filtering is deeply embedded in cross-cultural literary exchange and exerts a lasting influence on both the transmission and interpretation of literary works.This article examines the English translation of Ba Jin’s The Family by Sidney Shapiro,focusing on the manifestations and underlying causes of cultural filtering in the translated text.The translator adopts a range of strategies-including the addition of cultural annotations,selective omission,and abridged translation of certain content-to implement various forms of cultural filtering.These choices are shaped by multiple filtering processes,such as the translator’s cultural identity and his understanding of traditional Chinese culture.While cultural filtering in cross-cultural translation is inevitable and may result in partial loss of meaning,it can also breathe new life into the source text and facilitate mutual understanding and dialogue between different cultural systems.展开更多
Relation extraction plays a crucial role in numerous downstream tasks.Dialogue relation extraction focuses on identifying relations between two arguments within a given dialogue.To tackle the problem of low informatio...Relation extraction plays a crucial role in numerous downstream tasks.Dialogue relation extraction focuses on identifying relations between two arguments within a given dialogue.To tackle the problem of low information density in dialogues,methods based on trigger enhancement have been proposed,yielding positive results.However,trigger enhancement faces challenges,which cause suboptimal model performance.First,the proportion of annotated triggers is low in DialogRE.Second,feature representations of triggers and arguments often contain conflicting information.In this paper,we propose a novel Multi-Feature Filtering and Fusion trigger enhancement approach to overcome these limitations.We first obtain representations of arguments,and triggers that contain rich semantic information through attention and gate methods.Then,we design a feature filtering mechanism that eliminates conflicting features in the encoding of trigger prototype representations and their corresponding argument pairs.Additionally,we utilize large language models to create prompts based on Chain-of-Thought and In-context Learning for automated trigger extraction.Experiments show that our model increases the average F1 score by 1.3%in the dialogue relation extraction task.Ablation and case studies confirm the effectiveness of our model.Furthermore,the feature filtering method effectively integrates with other trigger enhancement models,enhancing overall performance and demonstrating its ability to resolve feature conflicts.展开更多
Optical wireless(OW)communication systems face significant challenges such as signal attenuation due to atmospheric absorption,scattering,and noise from hardware components,which degrade detection sensitivity.To addre...Optical wireless(OW)communication systems face significant challenges such as signal attenuation due to atmospheric absorption,scattering,and noise from hardware components,which degrade detection sensitivity.To address these challenges,we propose a digital processing algorithm that combines finite impulse response filtering with dynamic synchronization based on pulse addition and subtraction.Unlike conventional methods,which typically rely solely on hardware optimization or basic thresholding techniques,the proposed approach integrates filtering and synchronization to improve weak signal detection and reduce noise-induced errors.The proposed algorithm was implemented and verified using a field-programmable gate array.Experiments conducted in an indoor OW communication environment demonstrate that the proposed algorithm significantly improves detection sensitivity by approximately 6 dB and 5 dB at communication rates of 3.5 Mbps and 5.0 Mbps,respectively.Specifically,under darkroom conditions and a bit error rate of 1×10^(-7),the detection sensitivity was improved from-38.56 dBm to-44.77 dBm at 3.5 Mbps and from-37.12 dBm to-42.29 dBm at 5 Mbps.The proposed algorithm is crucial for future capture and tracking of signals at large dispersion angles and in underwater and long-distance communication scenarios.展开更多
How ecological and evolutionary factors affect small mammal diversity in arid regions remains largely unknown.Here,we combined the largest phylogeny and occurrence dataset of Gerbillinae desert rodents to explore the ...How ecological and evolutionary factors affect small mammal diversity in arid regions remains largely unknown.Here,we combined the largest phylogeny and occurrence dataset of Gerbillinae desert rodents to explore the underlying factors shaping present-day distribution patterns.In particular,we analyzed the relative contributions of ecological and evolutionary factors on their species diversity using a variety of models.Additionally,we inferred the ancestral range and possible dispersal scenarios and estimated the diversification rate of Gerbillinae.We found that Gerbillinae likely originated in the Horn of Africa in the Middle Miocene and then dispersed and diversified across arid regions in northern and southern Africa and western and central Asia,forming their current distribution pattern.Multiple ecological and evolutionary factors jointly determine the spatial pattern of Gerbillinae diversity,but evolutionary factors(evolutionary time and speciation rate)and habitat filtering were the most important in explaining the spatial variation in species richness.Our study enhances the understanding of the diversity patterns of small mammals in arid regions and highlights the importance of including evolutionary factors when interpreting the mechanisms underlying large-scale species diversity patterns.展开更多
Aluminum electrolyte capacitors(AEC)are widely used in AC filtering as traditional filter capacitors.However,their strong rigidity,high hardness,and high-risk factor have hindered the flexible development of filter ca...Aluminum electrolyte capacitors(AEC)are widely used in AC filtering as traditional filter capacitors.However,their strong rigidity,high hardness,and high-risk factor have hindered the flexible development of filter capacitors.Flexible supercapacitors,due to their high energy density and outstanding cycle stability,are becoming one of the main directions for the development of filter capacitors in the future.This paper self-assembles a MnO_(2)-based flexible supercapacitor with high area capacitance and fast frequency response,and preliminarily verifies the feasibility of using the capacitor for AC filtering through simulation tests in Multisim.Finally,the AC filtering test of the flexible supercapacitor using an oscilloscope demonstrates that the ripple factor in the range of 2.7%to 8%,which confirms that the MnO_(2)-based flexible supercapacitor has a great AC filtering function and can replace traditional aluminum electrolyte capacitors in AC filtering,promoting the flexible development of electronic products.展开更多
Recent theoretical verification of self-similar and dissipative pure-quartic solitons(PQSs)emphasized the similarity between PQS lasers and conventional fiber lasers,but the unique equilibrium mechanism hinders the fo...Recent theoretical verification of self-similar and dissipative pure-quartic solitons(PQSs)emphasized the similarity between PQS lasers and conventional fiber lasers,but the unique equilibrium mechanism hinders the formation of PQS molecules in normal fourth-order dispersion(FOD)regimes.In this paper,we investigated the effect of filters on shaping PQSs in normal FOD based on a passively mode-locked fiber laser model.A bandpass filter eliminates the time pedestal of dissipative PQSs,thus realizing a multi-pulsing state.When the filter bandwidth is appropriate,the effective spectral filtering effect can lower the pulse splitting threshold and enable the coherent restoration from chaotic PQSs to PQS molecules.Additionally,changing the central wavelength of the filter can generate PQSs and PQS molecules with asymmetric intensity distributions.These results are important guides for the manipulation of PQSs and the construction of high repetition-frequency fiber lasers.展开更多
Based on the superiority of adaptive filtering algorithms designed with hyperbolic function-like objective functions,this paper proposes generalized spline adaptive filtering(SAF)algorithms designed with hyperbolic fu...Based on the superiority of adaptive filtering algorithms designed with hyperbolic function-like objective functions,this paper proposes generalized spline adaptive filtering(SAF)algorithms designed with hyperbolic function-like objective functions.Specifically,a series of generalized new SAF algorithms are proposed by introducing the q-deformed hyperbolic function as the cost function,named SAF-qDHSI,SAF-qDHCO,SAFqDHTA&SAF-qDHSE algorithms,respectively.Then,the proposed algorithm is theoretically demonstrated with detailed mean convergence and computational complexity analysis;secondly,the effect of different q values on the performance of the new algorithm is verified through data simulation;the new algorithm still has better performance under the interference of Gaussian noise and non-Gaussian noise even when facing the system mutation;finally,the new algorithm is verified through the measured engineering data,and the results show that the new algorithm has better convergence and robustness compared with the existing algorithm.In conclusion,the generalized algorithm based on the new cost function proposed in this paper is more effective in nonlinear system identification.展开更多
文摘The robust H∞ filtering problem for uncertain discrete-time Markovian jump linear systems with mode- dependent time-delays is investigated. Attention is focused on designing a Markovian jump linear filter that ensures robust stochastic stability while achieving a prescribed H∞ performance level of the resulting filtering error system, for all admissible uncertainties. The key features of the approach include the introduction of a new type of stochastic Lyapunov functional and some free weighting matrix variables. Sufficient conditions for the solvability of this problem are obtained in terms of a set of linear matrix inequalities. Numerical examples are provided to demonstrate the reduced conservatism of the proposed approach.
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.
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the National Natural Science Foundation of China (60574001)Program for New CenturyExcellent Talents in University (NCET-05-0485) and PIRTJiangnan
文摘A novel H∞ design methodology for a neural network-based nonlinear filtering scheme is addressed. Firstly, neural networks are employed to approximate the nonlinearities. Next, the nonlinear dynamic system is represented by the mode-dependent linear difference inclusion （LDI）. Finally, based on the LDI model, a neural network-based nonlinear filter （NNBNF） is developed to minimize the upper bound of H∞ gain index of the estimation error under some linear matrix inequality （LMI） constraints. Compared with the existing nonlinear filters, NNBNF is time-invariant and numerically tractable. The validity and applicability of the proposed approach are successfully demonstrated in an illustrative example.
基金This work was supported by the National Natural Science Foundation of China(No.60574084)the National 863 Project(No.2006AA04Z428)the National 973 Program of China(No.2002CB312200).
文摘Robust H-infinity filtering for a class of uncertain discrete-time linear systems with time delays and missing measurements is studied in this paper. The uncertain parameters are supposed to reside in a convex polytope and the missing measurements are described by a binary switching sequence satisfying a Bernoulli distribution. Our attention is focused on the analysis and design of robust H-infinity filters such that, for all admissible parameter uncertainties and all possible missing measurements, the filtering error system is exponentially mean-square stable with a prescribed H-infinity disturbance attenuation level. A parameter-dependent approach is proposed to derive a less conservative result. Sufficient conditions are established for the existence of the desired filter in terms of certain linear matrix inequalities （LMIs）. When these LMIs are feasible, an explicit expression of the desired filter is also provided. Finally, a numerical example is presented to illustrate the effectiveness and applicability of the proposed method.
基金Sponsored by the Major Program of National Natural Science Foundation of China(Grant No.60710002)the Program for Changjiang Scholars and Innovative Research Team in University
文摘To obtain a stable and proper linear filter to make the filtering error system robustly and strictly passive, the problem of full-order robust passive filtering for continuous-time polytopic uncertain time-delay systems was investigated. A criterion for the passivity of time-delay systems was firstly provided in terms of linear matrix inequalities (LMI). Then an LMI sufficient condition for the existence of a robust filter was established and a design procedure was proposed for this type of systems. A numerical example demonstrated the feasibility of the filtering design procedure.
基金supported by the National Natural Science(No.U19A2063)the Jilin Provincial Development Program of Science and Technology (No.20230201080GX)the Jilin Province Education Department Scientific Research Project (No.JJKH20230851KJ)。
文摘The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions and are easy to lose detailed information.So we propose a rendered image denoising method with filtering guided by lighting information.First,we design an image segmentation algorithm based on lighting information to segment the image into different illumination areas.Then,we establish the parameter prediction model guided by lighting information for filtering(PGLF)to predict the filtering parameters of different illumination areas.For different illumination areas,we use these filtering parameters to construct area filters,and the filters are guided by the lighting information to perform sub-area filtering.Finally,the filtering results are fused with auxiliary features to output denoised images for improving the overall denoising effect of the image.Under the physically based rendering tool(PBRT)scene and Tungsten dataset,the experimental results show that compared with other guided filtering denoising methods,our method improves the peak signal-to-noise ratio(PSNR)metrics by 4.2164 dB on average and the structural similarity index(SSIM)metrics by 7.8%on average.This shows that our method can better reduce the noise in complex lighting scenesand improvethe imagequality.
基金Sponsored by the National Natural Science Foundation of China(Grant No.60574001)Program for New Century Excellent Talents in University(Grant No.NCET-05-0485)
文摘The problem of robust H∞ filtering for a class of neutral jump systems with time-delay and norm- bounded uncertainties is considered. By re-constructing the system, the dynamics of overall augmented error systems is obtained which involves unknown inputs represented by disturbances, model uncertainties and time-delays. As to the nominal system, sufficient conditions are provided for the existence of the mode-dependent H∞ filter by selecting the appropriate Lyapunov-Krasovskii function and the robust H∞ filter is proposed for the jump system while considering the time-delays and uncertainties. Both of above conditions for the existence of the H∞ filter and roust H∞ filter are presented in terms of linear matrix inequalities, and convex optimization problems are formulated to design the desired filters. By employing the proposed mode-dependent H∞ filter, the systems have the stochastic stability and better ability of restraining disturbances stochastically, and the given prescribed H∞ performance is guaranteed. Simulation resuhs illustrate the effectiveness of developed techniques.
基金supported by the National Key Research and Development Program of China (No.2019YFB2204302)。
文摘Although guided image filtering(GIF) is known for preserving edges and fast computation,it may produce inaccurate outputs in depth map restoration.In this paper,a novel confidence-weighted GIF called mutual-structure weighted GIF(MSWGIF) is proposed,which replaces the mean filtering strategy in GIF during handling overlapping windows.The confidence value is composed of a depth term and a mutual-structure term,where the depth term is utilized to protect the edges of the output,and the mutual-structure term helps to select accurate windows during the structure characteristics of the guidance image are transferred to the output.Experimental results show that MSWGIF reduces the root mean square error(RMSE) by an average of 12.37%,and the average growth rate of correlation(CORR) is 0.07% on average.Additionally,the average growth rate of structure similarity index measure(SSIM) is 0.34%.
基金Sponsored by the National Natural Science Foundation of China ( Grant No 60710002,60974044)Self-planned Task of State Key Laboratory of Robotics and System( Grant No SKLRS200801A03)
文摘This paper focuses on the problem of dissipative filtering for linear continuous-time polytopic uncertain time-delay systems. To obtain a stable and proper linear filter such that the filtering error system is strictly dissipative for all admissible uncertainties,a new dissipativity criterion which realizes separation between the Lyapunov matrices and the system dynamic matrices is firstly provided in terms of linear matrix inequalities ( LMI) . Then an LMI sufficient condition for the existence of a robust filter is established and a design procedure is proposed for this type of systems. One numerical example demonstrates less conservativeness of the proposed criterion,the other numerical example illustrates the validity of the proposed filter design.
文摘This study introduces an advanced recommender system for technology enhanced learning(TEL)that synergizes neural collaborative filtering,sentiment analysis,and an adaptive learning rate to address the limitations of traditional TEL systems.Recognizing the critical gap in existing approaches—primarily their neglect of user emotional feedback and static learning paths—our model innovatively incorporates sentiment analysis to capture and respond to nuanced emotional feedback from users.Utilizing bidirectional encoder representations from Transformers for sentiment analysis,our system not only understands but also respects user privacy by processing feedback without revealing sensitive information.The adaptive learning rate,inspired by AdaGrad,allows our model to adjust its learning trajectory based on the sentiment scores associated with user feedback,ensuring a dynamic response to both positive and negative sentiments.This dual approach enhances the system’s adapt-ability to changing user preferences and improves its contentment understanding.Our methodology involves a comprehensive analysis of both the content of learning materials and the behaviors and preferences of learners,facilitating a more personalized learning experience.By dynamically adjusting recommendations based on real-time user data and behavioral analysis,our system leverages the collective insights of similar users and rele-vant content.We validated our approach against three datasets-MovieLens,Amazon,and a proprietary TEL dataset—and saw significant improvements in recommendation precision,F-score,and mean absolute error.The results indicate the potential of integrating sentiment analysis and adaptive learning rates into TEL recommender systems,marking a step forward in developing more responsive and user-centric educational technologies.This study paves the way for future advancements in TEL systems,emphasizing the importance of emotional intelli-gence and adaptability in enhancing the learning experience.
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.
文摘Cultural filtering is deeply embedded in cross-cultural literary exchange and exerts a lasting influence on both the transmission and interpretation of literary works.This article examines the English translation of Ba Jin’s The Family by Sidney Shapiro,focusing on the manifestations and underlying causes of cultural filtering in the translated text.The translator adopts a range of strategies-including the addition of cultural annotations,selective omission,and abridged translation of certain content-to implement various forms of cultural filtering.These choices are shaped by multiple filtering processes,such as the translator’s cultural identity and his understanding of traditional Chinese culture.While cultural filtering in cross-cultural translation is inevitable and may result in partial loss of meaning,it can also breathe new life into the source text and facilitate mutual understanding and dialogue between different cultural systems.
基金supported by the National Key Research and Development Program of China(No.2023YFF0905400)the National Natural Science Foundation of China(No.U2341229).
文摘Relation extraction plays a crucial role in numerous downstream tasks.Dialogue relation extraction focuses on identifying relations between two arguments within a given dialogue.To tackle the problem of low information density in dialogues,methods based on trigger enhancement have been proposed,yielding positive results.However,trigger enhancement faces challenges,which cause suboptimal model performance.First,the proportion of annotated triggers is low in DialogRE.Second,feature representations of triggers and arguments often contain conflicting information.In this paper,we propose a novel Multi-Feature Filtering and Fusion trigger enhancement approach to overcome these limitations.We first obtain representations of arguments,and triggers that contain rich semantic information through attention and gate methods.Then,we design a feature filtering mechanism that eliminates conflicting features in the encoding of trigger prototype representations and their corresponding argument pairs.Additionally,we utilize large language models to create prompts based on Chain-of-Thought and In-context Learning for automated trigger extraction.Experiments show that our model increases the average F1 score by 1.3%in the dialogue relation extraction task.Ablation and case studies confirm the effectiveness of our model.Furthermore,the feature filtering method effectively integrates with other trigger enhancement models,enhancing overall performance and demonstrating its ability to resolve feature conflicts.
基金supported by National Key R&D Program of China under Grants No.2022YFB3902500,No.2022YFB2903402,and No.2021YFA0718804Natural Science Foundation of Jilin Province under Grant No.222621JC010297013Education Department of Jilin Province under Grant No.JJKH20220745KJ.
文摘Optical wireless(OW)communication systems face significant challenges such as signal attenuation due to atmospheric absorption,scattering,and noise from hardware components,which degrade detection sensitivity.To address these challenges,we propose a digital processing algorithm that combines finite impulse response filtering with dynamic synchronization based on pulse addition and subtraction.Unlike conventional methods,which typically rely solely on hardware optimization or basic thresholding techniques,the proposed approach integrates filtering and synchronization to improve weak signal detection and reduce noise-induced errors.The proposed algorithm was implemented and verified using a field-programmable gate array.Experiments conducted in an indoor OW communication environment demonstrate that the proposed algorithm significantly improves detection sensitivity by approximately 6 dB and 5 dB at communication rates of 3.5 Mbps and 5.0 Mbps,respectively.Specifically,under darkroom conditions and a bit error rate of 1×10^(-7),the detection sensitivity was improved from-38.56 dBm to-44.77 dBm at 3.5 Mbps and from-37.12 dBm to-42.29 dBm at 5 Mbps.The proposed algorithm is crucial for future capture and tracking of signals at large dispersion angles and in underwater and long-distance communication scenarios.
基金supported by grants from the Third Xinjiang Scientific Expedition Program(Grant No.2022xjkk0205 to Lin Xia,No.2021xjkk0604 to Jilong Cheng)the National Natural Science Foundation of China(32170416 to Qisen Yang,31900325 to Jilong Cheng)+1 种基金the Joint Fund of National Natural Science Foundation of China(U2003203 to Lin Xia)the Key Laboratory of Zoological Systematics and Evolution of the Chinese Academy of Sciences(Y229YX5105 to Qisen Yang).
文摘How ecological and evolutionary factors affect small mammal diversity in arid regions remains largely unknown.Here,we combined the largest phylogeny and occurrence dataset of Gerbillinae desert rodents to explore the underlying factors shaping present-day distribution patterns.In particular,we analyzed the relative contributions of ecological and evolutionary factors on their species diversity using a variety of models.Additionally,we inferred the ancestral range and possible dispersal scenarios and estimated the diversification rate of Gerbillinae.We found that Gerbillinae likely originated in the Horn of Africa in the Middle Miocene and then dispersed and diversified across arid regions in northern and southern Africa and western and central Asia,forming their current distribution pattern.Multiple ecological and evolutionary factors jointly determine the spatial pattern of Gerbillinae diversity,but evolutionary factors(evolutionary time and speciation rate)and habitat filtering were the most important in explaining the spatial variation in species richness.Our study enhances the understanding of the diversity patterns of small mammals in arid regions and highlights the importance of including evolutionary factors when interpreting the mechanisms underlying large-scale species diversity patterns.
文摘Aluminum electrolyte capacitors(AEC)are widely used in AC filtering as traditional filter capacitors.However,their strong rigidity,high hardness,and high-risk factor have hindered the flexible development of filter capacitors.Flexible supercapacitors,due to their high energy density and outstanding cycle stability,are becoming one of the main directions for the development of filter capacitors in the future.This paper self-assembles a MnO_(2)-based flexible supercapacitor with high area capacitance and fast frequency response,and preliminarily verifies the feasibility of using the capacitor for AC filtering through simulation tests in Multisim.Finally,the AC filtering test of the flexible supercapacitor using an oscilloscope demonstrates that the ripple factor in the range of 2.7%to 8%,which confirms that the MnO_(2)-based flexible supercapacitor has a great AC filtering function and can replace traditional aluminum electrolyte capacitors in AC filtering,promoting the flexible development of electronic products.
基金Project supported by the National Natural Science Foundation of China(Grant No.62175116)。
文摘Recent theoretical verification of self-similar and dissipative pure-quartic solitons(PQSs)emphasized the similarity between PQS lasers and conventional fiber lasers,but the unique equilibrium mechanism hinders the formation of PQS molecules in normal fourth-order dispersion(FOD)regimes.In this paper,we investigated the effect of filters on shaping PQSs in normal FOD based on a passively mode-locked fiber laser model.A bandpass filter eliminates the time pedestal of dissipative PQSs,thus realizing a multi-pulsing state.When the filter bandwidth is appropriate,the effective spectral filtering effect can lower the pulse splitting threshold and enable the coherent restoration from chaotic PQSs to PQS molecules.Additionally,changing the central wavelength of the filter can generate PQSs and PQS molecules with asymmetric intensity distributions.These results are important guides for the manipulation of PQSs and the construction of high repetition-frequency fiber lasers.
基金financially supported by the National Natural Science Foundation of China (8225041038)the Sichuan Science and Technology Program (23NSFSC2916)the Fundamental Research Funds for the Central Universities, Southwest Minzu University (ZYN2024077)
文摘Based on the superiority of adaptive filtering algorithms designed with hyperbolic function-like objective functions,this paper proposes generalized spline adaptive filtering(SAF)algorithms designed with hyperbolic function-like objective functions.Specifically,a series of generalized new SAF algorithms are proposed by introducing the q-deformed hyperbolic function as the cost function,named SAF-qDHSI,SAF-qDHCO,SAFqDHTA&SAF-qDHSE algorithms,respectively.Then,the proposed algorithm is theoretically demonstrated with detailed mean convergence and computational complexity analysis;secondly,the effect of different q values on the performance of the new algorithm is verified through data simulation;the new algorithm still has better performance under the interference of Gaussian noise and non-Gaussian noise even when facing the system mutation;finally,the new algorithm is verified through the measured engineering data,and the results show that the new algorithm has better convergence and robustness compared with the existing algorithm.In conclusion,the generalized algorithm based on the new cost function proposed in this paper is more effective in nonlinear system identification.
