In order to reduce the intrinsic interference of the filter bank multicarrier-quadrature amplitude modulation(FBMC-QAM)system,a novel filter optimization scheme based on discrete prolate spheroidal sequences(DPSS)is p...In order to reduce the intrinsic interference of the filter bank multicarrier-quadrature amplitude modulation(FBMC-QAM)system,a novel filter optimization scheme based on discrete prolate spheroidal sequences(DPSS)is proposed.Firstly,a prototype filter function based on DPSS is designed,since the eigenvalue can be used as an indicator of the energy concentration of DPSS,so a threshold is set,and the sequence with the most concentrated energy is selected under the threshold,that is,the sequence with the eigenvalue higher than the threshold,and the prototype filter function is rewritten as a weighted sum function of multiple eigenvectors.Under the energy constraints of the filter,the relationship between the eigenvectors and the intrinsic interference function is established,and the function problem is transformed into an optimization problem for the weighted coefficients.Through the interior point method,the most suitable weight is found to obtain the minimum intrinsic interference result.Theoretical analysis and simulation results show that compared with the prototype filters such as Type1 and CaseC,the DPSS filter applying the proposed optimization algorithm can effectively suppress the intrinsic interference of the system and obtain a better bit error rate(BER)performance.展开更多
Controlled thermonuclear reactors require consistent monitoring of plasma in the toroidal chamber.Better working conditions of such machines can be monitored by analyzing its radiations.Various wavelengths such as 656...Controlled thermonuclear reactors require consistent monitoring of plasma in the toroidal chamber.Better working conditions of such machines can be monitored by analyzing its radiations.Various wavelengths such as 656.3,486.1,464.7 nm are quite significant which are used for health monitoring of thermonuclear machines.The optical thinfilmfilters which work on construc-tive and destructive interference are the ideal choices.Thesefilters are multi-layered with a pair of high and low refractive index dielectric materials.Significantly high transmission index at the desired wavelength and relatively low transmission at the other wavelengths are desired.With this as the objective,it is necessary to design thefilter.Various optimization techniques are used for identifying the suitable design of thefilters.To choose the parameter combination that provides the most excellent performance,optimization of the design para-meters is entailed.The goal of this work is to improve the optical bandfilter using the Bald eagle search optimization(BES)method.The ideal design is determined by assessing several characteristics such as thickness,refractive index,Full-Width at Half-Maximum(FWHM),and the impact of choosing optical properties,which increases transmission potential.Initially,an alternate multi-layer stack with 28,30,and 32 layers is created by altering the thickness while keeping the dielectric substances high and low refractive indices constant.By adjusting the thickness of each layer,the BES algorithm achieves the best practical solution.The proposed method is implemented using MATLAB and the outcomes show the efficacy of the proposed technique.The transmittance,reflectance,and FWHM using the pro-posed BES are found to be 99.9356%,0.065%,and 1.2 nm respectively.展开更多
Target recognition and tracking is an important research filed in the surveillance industry.Traditional target recognition and tracking is to track moving objects, however, for the detected moving objects the specific...Target recognition and tracking is an important research filed in the surveillance industry.Traditional target recognition and tracking is to track moving objects, however, for the detected moving objects the specific content can not be determined.In this paper, a multi-target vehicle recognition and tracking algorithm based on YOLO v5 network architecture is proposed.The specific content of moving objects are identified by the network architecture, furthermore, the simulated annealing chaotic mechanism is embedded in particle swarm optimization-Gauss particle filter algorithm.The proposed simulated annealing chaotic particle swarm optimization-Gauss particle filter algorithm(SA-CPSO-GPF) is used to track moving objects.The experiment shows that the algorithm has a good tracking effect for the vehicle in the monitoring range.The root mean square error(RMSE), running time and accuracy of the proposed method are superior to traditional methods.The proposed algorithm has very good application value.展开更多
In this paper we present a filter-trust-region algorithm for solving LC1 unconstrained optimization problems which uses the second Dini upper directional derivative. We establish the global convergence of the algorith...In this paper we present a filter-trust-region algorithm for solving LC1 unconstrained optimization problems which uses the second Dini upper directional derivative. We establish the global convergence of the algorithm under reasonable assumptions.展开更多
In the present study,we propose to integrate the bilateral filter into the Shepard-interpolation-based method for the optimization of composite structures.The bilateral filter is used to avoid defects in the structure...In the present study,we propose to integrate the bilateral filter into the Shepard-interpolation-based method for the optimization of composite structures.The bilateral filter is used to avoid defects in the structure that may arise due to the gap/overlap of adjacent fiber tows or excessive curvature of fiber tows.According to the bilateral filter,sensitivities at design points in the filter area are smoothed by both domain filtering and range filtering.Then,the filtered sensitivities are used to update the design variables.Through several numerical examples,the effectiveness of the method was verified.展开更多
A compact tunable guided-mode resonant filter (GMRF) in the telecommunication region near the 1550 nm wave-length is proposed in this paper. Particle swarm optimization (PSO) is used to design the GMRF. The tunabi...A compact tunable guided-mode resonant filter (GMRF) in the telecommunication region near the 1550 nm wave-length is proposed in this paper. Particle swarm optimization (PSO) is used to design the GMRF. The tunability of the GMRF is achieved by an MEMS-based physical movement (in the horizontal or vertical direction) combined with an incident angle in a certain range. The results show that the resonant wavelength tuning of 110 nm (140mm) is obtained by horizontal movement of 168 nm (vertical movement of 435 nm) combined with an about 11° variation of incident angle.展开更多
This paper proposes a particle swarm optimization(PSO) based particle filter(PF) tracking framework,the embedded PSO makes particles move toward the high likelihood area to find the optimal position in the state t...This paper proposes a particle swarm optimization(PSO) based particle filter(PF) tracking framework,the embedded PSO makes particles move toward the high likelihood area to find the optimal position in the state transition stage,and simultaneously incorporates the newest observations into the proposal distribution in the update stage.In the proposed approach,likelihood measure functions involving multiple features are presented to enhance the performance of model fitting.Furthermore,the multi-feature weights are self-adaptively adjusted by a PSO algorithm throughout the tracking process.There are three main contributions.Firstly,the PSO algorithm is fused into the PF framework,which can efficiently alleviate the particles degeneracy phenomenon.Secondly,an effective convergence criterion for the PSO algorithm is explored,which can avoid particles getting stuck in local minima and maintain a greater particle diversity.Finally,a multi-feature weight self-adjusting strategy is proposed,which can significantly improve the tracking robustness and accuracy.Experiments performed on several challenging public video sequences demonstrate that the proposed tracking approach achieves a considerable performance.展开更多
A new method called satisfactory optimization method is proposed to design IIR (Infinite Impulse Response) digital filters, and the satisfactory optimization model is presented. The detailed algorithm of designing IIR...A new method called satisfactory optimization method is proposed to design IIR (Infinite Impulse Response) digital filters, and the satisfactory optimization model is presented. The detailed algorithm of designing IIR digital filters using satisfactory optimization method is described. By ~using quantum genetic algorithm characterized by rapid convergence and good global search capability, the satisfying solutions are ~achieved in the experiment of designing lowpass and bandpass IIR digital filters. Experimental results show that the performances of IIR filters designed by the introduced method are better than those by traditional methods.展开更多
In this paper, a new method of filtering for Lipschitz nonlinear systems is proposed in the form of an LMI optimization problem. The proposed filter has guaranteed decay rate (exponential convergence) and is robust ag...In this paper, a new method of filtering for Lipschitz nonlinear systems is proposed in the form of an LMI optimization problem. The proposed filter has guaranteed decay rate (exponential convergence) and is robust against unknown exogenous disturbance. In addition, thanks to the linearity of the proposed LMIs in the admissible Lipschitz constant, it can be maximized via LMI optimization. This adds an extra important feature to the observer, robustness against nonlinear uncertainty. Explicit bound on the tolerable nonlinear uncertainty is derived. The new LMI formulation also allows optimizations over the disturbance attenuation level ( cost). Then, the admissible Lipschitz constant and the disturbance attenuation level of the filter are simultaneously optimized through LMI multiobjective optimization.展开更多
Multi-carrier faster-than-Nyquist(MFTN)can improve the spectrum efficiency(SE).In this paper,we first analyze the benefit of time frequency packing MFTN(TFP-MFTN).Then,we propose an efficient digital implementation fo...Multi-carrier faster-than-Nyquist(MFTN)can improve the spectrum efficiency(SE).In this paper,we first analyze the benefit of time frequency packing MFTN(TFP-MFTN).Then,we propose an efficient digital implementation for TFP-MFTN based on filter bank multicarrier modulation.The time frequency packing ratio pair in our proposed implementation scheme is optimized with the SE criterion.Next,the joint optimization for the coded modulation MFTN based on extrinsic information transfer(EXIT)chart is performed.The Monte-Carlo simulations are carried out to verify performance gain of the joint inner and outer code optimization.Simulation results demonstrate that the TFPMFTN has a 0.8 dB and 0.9 dB gain comparing to time packing MFTN(TP-MFTN)and higher order Nyquist at same SE,respectively;the TFP-MFTN with optimized low density parity check(LDPC)code has a 2.9 dB gain comparing to that with digital video broadcasting(DVB)LDPC.Compared with previous work on TFP-MFTN(SE=1.55 bit/s/Hz),the SE of our work is improved by 29%and our work has a 4.1 dB gain at BER=1×10^(-5).展开更多
The nonlinear filtering problem has enduringly been an active research topic in both academia and industry due to its ever-growing theoretical importance and practical significance.The main objective of nonlinear filt...The nonlinear filtering problem has enduringly been an active research topic in both academia and industry due to its ever-growing theoretical importance and practical significance.The main objective of nonlinear filtering is to infer the states of a nonlinear dynamical system of interest based on the available noisy measurements. In recent years, the advance of network communication technology has not only popularized the networked systems with apparent advantages in terms of installation,cost and maintenance, but also brought about a series of challenges to the design of nonlinear filtering algorithms, among which the communication constraint has been recognized as a dominating concern. In this context, a great number of investigations have been launched towards the networked nonlinear filtering problem with communication constraints, and many samplebased nonlinear filters have been developed to deal with the highly nonlinear and/or non-Gaussian scenarios. The aim of this paper is to provide a timely survey about the recent advances on the sample-based networked nonlinear filtering problem from the perspective of communication constraints. More specifically, we first review three important families of sample-based filtering methods known as the unscented Kalman filter, particle filter,and maximum correntropy filter. Then, the latest developments are surveyed with stress on the topics regarding incomplete/imperfect information, limited resources and cyber security.Finally, several challenges and open problems are highlighted to shed some lights on the possible trends of future research in this realm.展开更多
This paper describes the mitigation of harmonics in source and neutral current in three phase four wire system based on 4-leg shunt active power filter under balanced and unbalanced load conditions. Particle Swarm Opt...This paper describes the mitigation of harmonics in source and neutral current in three phase four wire system based on 4-leg shunt active power filter under balanced and unbalanced load conditions. Particle Swarm Optimization (PSO) and conventional Proportional Integral (PI) controller are used as control techniques to analyze the control performance of 4-leg shunt active power filter. The synchronous reference frame (SRF) method is used to extract reference current in 4-leg shunt active filter. The Hysteresis Current Controller (HCC) is used to generate gate pulses for Voltage Source Inverter (VSI) based 4-leg shunt active power filter. The proposed PSO technique gives less percentage of Total Harmonic Distortion (THD) value in source and neutral current and settling time of the DC capacitor voltage compared to conventional PI controller technique. The model of the proposed system performance was validated using MATLAB/Simulink environment.展开更多
In a limited number of ensembles, some samples do not adequately reflect the true atmospheric state and can in turn affect forecast performance. This study explored the feasibility of sample optimization using the ens...In a limited number of ensembles, some samples do not adequately reflect the true atmospheric state and can in turn affect forecast performance. This study explored the feasibility of sample optimization using the ensemble Kalman filter(EnKF) for a simulation of the 2014 Super Typhoon Rammasun, which made landfall in southern China in July 2014. Under the premise of sufficient ensemble spread, keeping samples with a good fit to observations and eliminating those with poor fit can affect the performance of En KF. In the sample optimization, states were selected based on the sample spatial correlation between the ensemble state and observations. The method discarded ensemble states that were less representative and, to maintain the overall ensemble size, generated new ensemble states by reproducing them from ensemble states with a good fit by adding random noise. Sample selection was performed based on radar echo data. Results showed that applying En KF with optimized samples improved the estimated track, intensity,precipitation distribution, and inner-core structure of Typhoon Rammasun. Therefore, the authors proposed that distinguishing between samples with good and poor fits is vital for ensemble prediction, suggesting that sample optimization is necessary to the effective use of En KF.展开更多
This paper deals with an optimization design method for the Gabor filters based on the analysis of an iris texture model. By means of analyzing the properties of an iris texture image, the energy distribution regulari...This paper deals with an optimization design method for the Gabor filters based on the analysis of an iris texture model. By means of analyzing the properties of an iris texture image, the energy distribution regularity of the iris texture image measured by the average power spectrum density is exploited, and the theoretical ranges of the efficient valued frequency and orientation parameters can also be deduced. The analysis shows that the energy distribution of the iris texture is generally centralized around lower frequencies in the spatial frequency domain. Accordingly, an iterative algorithm is designed to optimize the Gabor parameter field. The experimental results indicate the validity of the theory and efficiency of the algorithm.展开更多
Near-infrared (NIR) spectroscopy combined with chemometrics methods was applied to the rapid and reagent-free analysis of serum urea nitrogen (SUN). The mul-partitions modeling was performed to achieve parameter stabi...Near-infrared (NIR) spectroscopy combined with chemometrics methods was applied to the rapid and reagent-free analysis of serum urea nitrogen (SUN). The mul-partitions modeling was performed to achieve parameter stability. A large-scale parameter cyclic and global optimization platform for Norris derivative filter (NDF) of three parameters (the derivative order: d, the number of smoothing points: s and the number of differential gaps: g) was developed with PLS regression. Meantime, the parameters’ adaptive analysis of NDF algorithm was also given, and achieved a significantly better modeling effect than one without spectral pre-processing. After eliminating the interference wavebands of saturated absorption, the modeling performance was further improved. In validation, the root mean square error (SEP), correlation coefficient (RP) for prediction and the ratio of performance to deviation (RPD) were 1.66 mmol?L-1, 0.966 and 4.7, respectively. The results showed that the high-precision analysis of SUN was feasibility based on NIR spectroscopy and Norris-PLS. The global optimization method of NDF is also expected to be applied to other analysis objects.展开更多
Considering the soft constraint characteristics of voltage constraints, the Interior-Point Filter Algorithm is applied to solve the formulation of fuzzy model for the power system reactive power optimization with a la...Considering the soft constraint characteristics of voltage constraints, the Interior-Point Filter Algorithm is applied to solve the formulation of fuzzy model for the power system reactive power optimization with a large number of equality and inequality constraints. Based on the primal-dual interior-point algorithm, the algorithm maintains an updating “filter” at each iteration in order to decide whether to admit correction of iteration point which can avoid effectively oscillation due to the conflict between the decrease of objective function and the satisfaction of constraints and ensure the global convergence. Moreover, the “filter” improves computational efficiency because it filters the unnecessary iteration points. The calculation results of a practical power system indicate that the algorithm can effectively deal with the large number of inequality constraints of the fuzzy model of reactive power optimization and satisfy the requirement of online calculation which realizes to decrease the network loss and maintain specified margins of voltage.展开更多
In this paper, a model of topology optimization with linear buckling constraints is established based on an independent and continuous mapping method to minimize the plate/shell structure weight. A composite exponenti...In this paper, a model of topology optimization with linear buckling constraints is established based on an independent and continuous mapping method to minimize the plate/shell structure weight. A composite exponential function(CEF) is selected as filtering functions for element weight, the element stiffness matrix and the element geometric stiffness matrix, which recognize the design variables, and to implement the changing process of design variables from“discrete” to “continuous” and back to “discrete”. The buckling constraints are approximated as explicit formulations based on the Taylor expansion and the filtering function. The optimization model is transformed to dual programming and solved by the dual sequence quadratic programming algorithm. Finally, three numerical examples with power function and CEF as filter function are analyzed and discussed to demonstrate the feasibility and efficiency of the proposed method.展开更多
In this paper, an adaptive estimation algorithm is proposed for non-linear dynamic systems with unknown static parameters based on combination of particle filtering and Simultaneous Perturbation Stochastic Approxi- ma...In this paper, an adaptive estimation algorithm is proposed for non-linear dynamic systems with unknown static parameters based on combination of particle filtering and Simultaneous Perturbation Stochastic Approxi- mation (SPSA) technique. The estimations of parameters are obtained by maximum-likelihood estimation and sampling within particle filtering framework, and the SPSA is used for stochastic optimization and to approximate the gradient of the cost function. The proposed algorithm achieves combined estimation of dynamic state and static parameters of nonlinear systems. Simulation result demonstrates the feasibilitv and efficiency of the proposed algorithm展开更多
This paper proposes a method to design multichannel cosine modulated filter bank for image compression using multiobjective optimization technique. The design problem is a combination of stopband residual energy, leas...This paper proposes a method to design multichannel cosine modulated filter bank for image compression using multiobjective optimization technique. The design problem is a combination of stopband residual energy, least square error of the overall transfer function of the filter bank, coding gain with dc leakage free condition as constraint. The proposed algorithm uses Non-dominated Sorting Genetic Algorithm (NSGA) to minimize the mutually contradictory objective function by minimizing filter tap weights of prototype filter. The algorithm solves this problem by searching solutions that achieve the best compromise between the different objectives criteria. The performance of this algorithm is evaluated in terms of coding gain and peak signal to noise ratio (PSNR). Simulation results on different images are included to illustrate the effectiveness of the proposed algorithm for image compression application.展开更多
基金the National Natural Science Foundation of China(No.61601296,61201244)the Science and Technology Innovation Action Plan Project of Shanghai Science and Technology Commission(No.20511103500)the Talent Program of Shanghai University of Engineering Science(No.2018RC43)。
文摘In order to reduce the intrinsic interference of the filter bank multicarrier-quadrature amplitude modulation(FBMC-QAM)system,a novel filter optimization scheme based on discrete prolate spheroidal sequences(DPSS)is proposed.Firstly,a prototype filter function based on DPSS is designed,since the eigenvalue can be used as an indicator of the energy concentration of DPSS,so a threshold is set,and the sequence with the most concentrated energy is selected under the threshold,that is,the sequence with the eigenvalue higher than the threshold,and the prototype filter function is rewritten as a weighted sum function of multiple eigenvectors.Under the energy constraints of the filter,the relationship between the eigenvectors and the intrinsic interference function is established,and the function problem is transformed into an optimization problem for the weighted coefficients.Through the interior point method,the most suitable weight is found to obtain the minimum intrinsic interference result.Theoretical analysis and simulation results show that compared with the prototype filters such as Type1 and CaseC,the DPSS filter applying the proposed optimization algorithm can effectively suppress the intrinsic interference of the system and obtain a better bit error rate(BER)performance.
文摘Controlled thermonuclear reactors require consistent monitoring of plasma in the toroidal chamber.Better working conditions of such machines can be monitored by analyzing its radiations.Various wavelengths such as 656.3,486.1,464.7 nm are quite significant which are used for health monitoring of thermonuclear machines.The optical thinfilmfilters which work on construc-tive and destructive interference are the ideal choices.Thesefilters are multi-layered with a pair of high and low refractive index dielectric materials.Significantly high transmission index at the desired wavelength and relatively low transmission at the other wavelengths are desired.With this as the objective,it is necessary to design thefilter.Various optimization techniques are used for identifying the suitable design of thefilters.To choose the parameter combination that provides the most excellent performance,optimization of the design para-meters is entailed.The goal of this work is to improve the optical bandfilter using the Bald eagle search optimization(BES)method.The ideal design is determined by assessing several characteristics such as thickness,refractive index,Full-Width at Half-Maximum(FWHM),and the impact of choosing optical properties,which increases transmission potential.Initially,an alternate multi-layer stack with 28,30,and 32 layers is created by altering the thickness while keeping the dielectric substances high and low refractive indices constant.By adjusting the thickness of each layer,the BES algorithm achieves the best practical solution.The proposed method is implemented using MATLAB and the outcomes show the efficacy of the proposed technique.The transmittance,reflectance,and FWHM using the pro-posed BES are found to be 99.9356%,0.065%,and 1.2 nm respectively.
基金Supported by the National Key R&D Plan of China (2021YFE0105000)the National Natural Science Foundation of China (52074213)+1 种基金Shaanxi Key R&D Plan Project (2021SF-472)Yulin Science and Technology Plan Project (CXY-2020-036)。
文摘Target recognition and tracking is an important research filed in the surveillance industry.Traditional target recognition and tracking is to track moving objects, however, for the detected moving objects the specific content can not be determined.In this paper, a multi-target vehicle recognition and tracking algorithm based on YOLO v5 network architecture is proposed.The specific content of moving objects are identified by the network architecture, furthermore, the simulated annealing chaotic mechanism is embedded in particle swarm optimization-Gauss particle filter algorithm.The proposed simulated annealing chaotic particle swarm optimization-Gauss particle filter algorithm(SA-CPSO-GPF) is used to track moving objects.The experiment shows that the algorithm has a good tracking effect for the vehicle in the monitoring range.The root mean square error(RMSE), running time and accuracy of the proposed method are superior to traditional methods.The proposed algorithm has very good application value.
基金Supported by CERG: CityU 101005 of the Government of Hong Kong SAR, Chinathe National Natural ScienceFoundation of China, the Specialized Research Fund of Doctoral Program of Higher Education of China (Grant No.20040319003)the Natural Science Fund of Jiangsu Province of China (Grant No. BK2006214)
文摘In this paper we present a filter-trust-region algorithm for solving LC1 unconstrained optimization problems which uses the second Dini upper directional derivative. We establish the global convergence of the algorithm under reasonable assumptions.
基金This research work was supported by the National Natural Science Foundation of China(Grant No.51975227)the Natural Science Foundation for Distinguished Young Scholars of Hubei Province,China(Grant No.2017CFA044).
文摘In the present study,we propose to integrate the bilateral filter into the Shepard-interpolation-based method for the optimization of composite structures.The bilateral filter is used to avoid defects in the structure that may arise due to the gap/overlap of adjacent fiber tows or excessive curvature of fiber tows.According to the bilateral filter,sensitivities at design points in the filter area are smoothed by both domain filtering and range filtering.Then,the filtered sensitivities are used to update the design variables.Through several numerical examples,the effectiveness of the method was verified.
基金Project supported by the National High-Tech Research and Development Program of China(Grant No.2011 AA050518)
文摘A compact tunable guided-mode resonant filter (GMRF) in the telecommunication region near the 1550 nm wave-length is proposed in this paper. Particle swarm optimization (PSO) is used to design the GMRF. The tunability of the GMRF is achieved by an MEMS-based physical movement (in the horizontal or vertical direction) combined with an incident angle in a certain range. The results show that the resonant wavelength tuning of 110 nm (140mm) is obtained by horizontal movement of 168 nm (vertical movement of 435 nm) combined with an about 11° variation of incident angle.
基金supported by the Chinese Ministry of Science and Intergovernmental Cooperation Project (2009DFA12870)the National Science Foundation of China (60974062,60972119)
文摘This paper proposes a particle swarm optimization(PSO) based particle filter(PF) tracking framework,the embedded PSO makes particles move toward the high likelihood area to find the optimal position in the state transition stage,and simultaneously incorporates the newest observations into the proposal distribution in the update stage.In the proposed approach,likelihood measure functions involving multiple features are presented to enhance the performance of model fitting.Furthermore,the multi-feature weights are self-adaptively adjusted by a PSO algorithm throughout the tracking process.There are three main contributions.Firstly,the PSO algorithm is fused into the PF framework,which can efficiently alleviate the particles degeneracy phenomenon.Secondly,an effective convergence criterion for the PSO algorithm is explored,which can avoid particles getting stuck in local minima and maintain a greater particle diversity.Finally,a multi-feature weight self-adjusting strategy is proposed,which can significantly improve the tracking robustness and accuracy.Experiments performed on several challenging public video sequences demonstrate that the proposed tracking approach achieves a considerable performance.
文摘A new method called satisfactory optimization method is proposed to design IIR (Infinite Impulse Response) digital filters, and the satisfactory optimization model is presented. The detailed algorithm of designing IIR digital filters using satisfactory optimization method is described. By ~using quantum genetic algorithm characterized by rapid convergence and good global search capability, the satisfying solutions are ~achieved in the experiment of designing lowpass and bandpass IIR digital filters. Experimental results show that the performances of IIR filters designed by the introduced method are better than those by traditional methods.
基金Supported by National Basic Research Program of China (973 Program) (2009CB320604), State Key Program of National Natural Science Foundation of China (60534010), National Natural Science Foundation of China (60674021), Funds for Creative Research Groups of China (60821063), the 111 Project (B08015), and the Funds of Doctoral Program of Ministry of Education of China (20060145019)
文摘In this paper, a new method of filtering for Lipschitz nonlinear systems is proposed in the form of an LMI optimization problem. The proposed filter has guaranteed decay rate (exponential convergence) and is robust against unknown exogenous disturbance. In addition, thanks to the linearity of the proposed LMIs in the admissible Lipschitz constant, it can be maximized via LMI optimization. This adds an extra important feature to the observer, robustness against nonlinear uncertainty. Explicit bound on the tolerable nonlinear uncertainty is derived. The new LMI formulation also allows optimizations over the disturbance attenuation level ( cost). Then, the admissible Lipschitz constant and the disturbance attenuation level of the filter are simultaneously optimized through LMI multiobjective optimization.
基金supported by the National Natural Science Foundation of China(61961014,61561017)。
文摘Multi-carrier faster-than-Nyquist(MFTN)can improve the spectrum efficiency(SE).In this paper,we first analyze the benefit of time frequency packing MFTN(TFP-MFTN).Then,we propose an efficient digital implementation for TFP-MFTN based on filter bank multicarrier modulation.The time frequency packing ratio pair in our proposed implementation scheme is optimized with the SE criterion.Next,the joint optimization for the coded modulation MFTN based on extrinsic information transfer(EXIT)chart is performed.The Monte-Carlo simulations are carried out to verify performance gain of the joint inner and outer code optimization.Simulation results demonstrate that the TFPMFTN has a 0.8 dB and 0.9 dB gain comparing to time packing MFTN(TP-MFTN)and higher order Nyquist at same SE,respectively;the TFP-MFTN with optimized low density parity check(LDPC)code has a 2.9 dB gain comparing to that with digital video broadcasting(DVB)LDPC.Compared with previous work on TFP-MFTN(SE=1.55 bit/s/Hz),the SE of our work is improved by 29%and our work has a 4.1 dB gain at BER=1×10^(-5).
基金supported in part by the National Key R&D Program of China (2022ZD0116401,2022ZD0116400)the National Natural Science Foundation of China (62203016,U2241214,T2121002,62373008,61933007)+2 种基金the China Postdoctoral Science Foundation (2021TQ0009)the Royal Society of the UKthe Alexander von Humboldt Foundation of Germany。
文摘The nonlinear filtering problem has enduringly been an active research topic in both academia and industry due to its ever-growing theoretical importance and practical significance.The main objective of nonlinear filtering is to infer the states of a nonlinear dynamical system of interest based on the available noisy measurements. In recent years, the advance of network communication technology has not only popularized the networked systems with apparent advantages in terms of installation,cost and maintenance, but also brought about a series of challenges to the design of nonlinear filtering algorithms, among which the communication constraint has been recognized as a dominating concern. In this context, a great number of investigations have been launched towards the networked nonlinear filtering problem with communication constraints, and many samplebased nonlinear filters have been developed to deal with the highly nonlinear and/or non-Gaussian scenarios. The aim of this paper is to provide a timely survey about the recent advances on the sample-based networked nonlinear filtering problem from the perspective of communication constraints. More specifically, we first review three important families of sample-based filtering methods known as the unscented Kalman filter, particle filter,and maximum correntropy filter. Then, the latest developments are surveyed with stress on the topics regarding incomplete/imperfect information, limited resources and cyber security.Finally, several challenges and open problems are highlighted to shed some lights on the possible trends of future research in this realm.
文摘This paper describes the mitigation of harmonics in source and neutral current in three phase four wire system based on 4-leg shunt active power filter under balanced and unbalanced load conditions. Particle Swarm Optimization (PSO) and conventional Proportional Integral (PI) controller are used as control techniques to analyze the control performance of 4-leg shunt active power filter. The synchronous reference frame (SRF) method is used to extract reference current in 4-leg shunt active filter. The Hysteresis Current Controller (HCC) is used to generate gate pulses for Voltage Source Inverter (VSI) based 4-leg shunt active power filter. The proposed PSO technique gives less percentage of Total Harmonic Distortion (THD) value in source and neutral current and settling time of the DC capacitor voltage compared to conventional PI controller technique. The model of the proposed system performance was validated using MATLAB/Simulink environment.
基金National Key Project for Basic Research(973 project)(2015CB452802)National Natural Science Fund(41475102,41675099,41475061)+2 种基金Science and Technology Planning Project of Guangdong Province(2017B020218003,2017B030314140)Natural Science Foundation of Guangdong Province(2016A030313140,2017A030313225)Science and technology project of Guangdong Meteorological Bureau(GRMC2017Q01)
文摘In a limited number of ensembles, some samples do not adequately reflect the true atmospheric state and can in turn affect forecast performance. This study explored the feasibility of sample optimization using the ensemble Kalman filter(EnKF) for a simulation of the 2014 Super Typhoon Rammasun, which made landfall in southern China in July 2014. Under the premise of sufficient ensemble spread, keeping samples with a good fit to observations and eliminating those with poor fit can affect the performance of En KF. In the sample optimization, states were selected based on the sample spatial correlation between the ensemble state and observations. The method discarded ensemble states that were less representative and, to maintain the overall ensemble size, generated new ensemble states by reproducing them from ensemble states with a good fit by adding random noise. Sample selection was performed based on radar echo data. Results showed that applying En KF with optimized samples improved the estimated track, intensity,precipitation distribution, and inner-core structure of Typhoon Rammasun. Therefore, the authors proposed that distinguishing between samples with good and poor fits is vital for ensemble prediction, suggesting that sample optimization is necessary to the effective use of En KF.
文摘This paper deals with an optimization design method for the Gabor filters based on the analysis of an iris texture model. By means of analyzing the properties of an iris texture image, the energy distribution regularity of the iris texture image measured by the average power spectrum density is exploited, and the theoretical ranges of the efficient valued frequency and orientation parameters can also be deduced. The analysis shows that the energy distribution of the iris texture is generally centralized around lower frequencies in the spatial frequency domain. Accordingly, an iterative algorithm is designed to optimize the Gabor parameter field. The experimental results indicate the validity of the theory and efficiency of the algorithm.
文摘Near-infrared (NIR) spectroscopy combined with chemometrics methods was applied to the rapid and reagent-free analysis of serum urea nitrogen (SUN). The mul-partitions modeling was performed to achieve parameter stability. A large-scale parameter cyclic and global optimization platform for Norris derivative filter (NDF) of three parameters (the derivative order: d, the number of smoothing points: s and the number of differential gaps: g) was developed with PLS regression. Meantime, the parameters’ adaptive analysis of NDF algorithm was also given, and achieved a significantly better modeling effect than one without spectral pre-processing. After eliminating the interference wavebands of saturated absorption, the modeling performance was further improved. In validation, the root mean square error (SEP), correlation coefficient (RP) for prediction and the ratio of performance to deviation (RPD) were 1.66 mmol?L-1, 0.966 and 4.7, respectively. The results showed that the high-precision analysis of SUN was feasibility based on NIR spectroscopy and Norris-PLS. The global optimization method of NDF is also expected to be applied to other analysis objects.
文摘Considering the soft constraint characteristics of voltage constraints, the Interior-Point Filter Algorithm is applied to solve the formulation of fuzzy model for the power system reactive power optimization with a large number of equality and inequality constraints. Based on the primal-dual interior-point algorithm, the algorithm maintains an updating “filter” at each iteration in order to decide whether to admit correction of iteration point which can avoid effectively oscillation due to the conflict between the decrease of objective function and the satisfaction of constraints and ensure the global convergence. Moreover, the “filter” improves computational efficiency because it filters the unnecessary iteration points. The calculation results of a practical power system indicate that the algorithm can effectively deal with the large number of inequality constraints of the fuzzy model of reactive power optimization and satisfy the requirement of online calculation which realizes to decrease the network loss and maintain specified margins of voltage.
基金supported by the National Natural Science Foundation of China(Grants 11072009,111720131)
文摘In this paper, a model of topology optimization with linear buckling constraints is established based on an independent and continuous mapping method to minimize the plate/shell structure weight. A composite exponential function(CEF) is selected as filtering functions for element weight, the element stiffness matrix and the element geometric stiffness matrix, which recognize the design variables, and to implement the changing process of design variables from“discrete” to “continuous” and back to “discrete”. The buckling constraints are approximated as explicit formulations based on the Taylor expansion and the filtering function. The optimization model is transformed to dual programming and solved by the dual sequence quadratic programming algorithm. Finally, three numerical examples with power function and CEF as filter function are analyzed and discussed to demonstrate the feasibility and efficiency of the proposed method.
基金the National Natural Science Foundation of China (No. 60404011)
文摘In this paper, an adaptive estimation algorithm is proposed for non-linear dynamic systems with unknown static parameters based on combination of particle filtering and Simultaneous Perturbation Stochastic Approxi- mation (SPSA) technique. The estimations of parameters are obtained by maximum-likelihood estimation and sampling within particle filtering framework, and the SPSA is used for stochastic optimization and to approximate the gradient of the cost function. The proposed algorithm achieves combined estimation of dynamic state and static parameters of nonlinear systems. Simulation result demonstrates the feasibilitv and efficiency of the proposed algorithm
文摘This paper proposes a method to design multichannel cosine modulated filter bank for image compression using multiobjective optimization technique. The design problem is a combination of stopband residual energy, least square error of the overall transfer function of the filter bank, coding gain with dc leakage free condition as constraint. The proposed algorithm uses Non-dominated Sorting Genetic Algorithm (NSGA) to minimize the mutually contradictory objective function by minimizing filter tap weights of prototype filter. The algorithm solves this problem by searching solutions that achieve the best compromise between the different objectives criteria. The performance of this algorithm is evaluated in terms of coding gain and peak signal to noise ratio (PSNR). Simulation results on different images are included to illustrate the effectiveness of the proposed algorithm for image compression application.