Perceptual auditory filter banks such as Bark-scale filter bank are widely used as front-end processing in speech recognition systems.However,the problem of the design of optimized filter banks that provide higher acc...Perceptual auditory filter banks such as Bark-scale filter bank are widely used as front-end processing in speech recognition systems.However,the problem of the design of optimized filter banks that provide higher accuracy in recognition tasks is still open.Owing to spectral analysis in feature extraction,an adaptive bands filter bank (ABFB) is presented.The design adopts flexible bandwidths and center frequencies for the frequency responses of the filters and utilizes genetic algorithm (GA) to optimize the design parameters.The optimization process is realized by combining the front-end filter bank with the back-end recognition network in the performance evaluation loop.The deployment of ABFB together with zero-crossing peak amplitude (ZCPA) feature as a front process for radial basis function (RBF) system shows significant improvement in robustness compared with the Bark-scale filter bank.In ABFB,several sub-bands are still more concentrated toward lower frequency but their exact locations are determined by the performance rather than the perceptual criteria.For the ease of optimization,only symmetrical bands are considered here,which still provide satisfactory results.展开更多
This paper proposes an estimation method of the directions of arrival(DOA) for the broadband signals received by a uniform planar antenna array including the mutual coupling effect. The process modeling of antenna arr...This paper proposes an estimation method of the directions of arrival(DOA) for the broadband signals received by a uniform planar antenna array including the mutual coupling effect. The process modeling of antenna array receiving dynamic signal is obtained accurately via building the array system electromagnetic space-time model, and the mutual coupling effect is included in the synthesis procedure automatically. The broadband signal is divided into several sub-bands, and the complex weight of these sub-bands frequencies is figured out using the least mean square iteration programming. In the proposed method, the mutual coupling effect is compensated at the different frequencies. The calculation results show that the method is suitable for the uniform linear and uniform circular array pattern integration, and it is commendably satisfied with the requirement of engineering design.展开更多
In this paper, the simultaneous perturbation stochastic approximation （SPSA） algorithm is used for seeking optimal parameters in an adaptive filter developed for assimilating observations in the very high dimensiona...In this paper, the simultaneous perturbation stochastic approximation （SPSA） algorithm is used for seeking optimal parameters in an adaptive filter developed for assimilating observations in the very high dimensional dynamical systems. The main results show that the SPSA is capable of yielding the high filter performance similar to that produced by classical optimization algorithms, with better performance for non-linear filtering problems as more and more observations are assimilated. The advantage of the SPSA is that at each iteration it requires only two measurements of the objective function to approximate the gradient vector regardless of the dimension of the control vector （or maximally, three measurements if second-order optimization algorithms are used）. The SPSA approach is thus free from the need to develop a discrete adjoint of tangent linear model as it is required up to now for solving optimization problems in very high dimensional systems. This technique offers promising perspectives on developing optimal assimilation systems encountered in the field of data assimilation in meteorology and oceanography.展开更多
To preserve the original signal as much as possible and filter random noises as many as possible in image processing,a threshold optimization-based adaptive template filtering algorithm was proposed.Unlike conventiona...To preserve the original signal as much as possible and filter random noises as many as possible in image processing,a threshold optimization-based adaptive template filtering algorithm was proposed.Unlike conventional filters whose template shapes and coefficients were fixed,multi-templates were defined and the right template for each pixel could be matched adaptively based on local image characteristics in the proposed method.The superiority of this method was verified by former results concerning the matching experiment of actual image with the comparison of conventional filtering methods.The adaptive search ability of immune genetic algorithm with the elitist selection and elitist crossover(IGAE) was used to optimize threshold t of the transformation function,and then combined with wavelet transformation to estimate noise variance.Multi-experiments were performed to test the validity of IGAE.The results show that the filtered result of t obtained by IGAE is superior to that of t obtained by other methods,IGAE has a faster convergence speed and a higher computational efficiency compared with the canonical genetic algorithm with the elitism and the immune algorithm with the information entropy and elitism by multi-experiments.展开更多
The filter-rods were supplied through compressed air conveyed to cigarette-maker by transmitter in my factory. Usually, each maker has two feed-pipes, it adopts fixed and one-to-one fashion, with the flexible manufact...The filter-rods were supplied through compressed air conveyed to cigarette-maker by transmitter in my factory. Usually, each maker has two feed-pipes, it adopts fixed and one-to-one fashion, with the flexible manufacturing system extending, and it＇s original fashion unable to satisfy the needs of a wide range of cigarette brands already, so it cry for a viable and reliable substitute. This paper creatively bring forward the optimized fashion of duct net about filter-rods based on topology structure, it adopts Freud＇s algorithm and improved-separated algorithm in order to achieve the optimized route, it has a apparent effect to improve the transport stability and reduce the transport time of filter- rods.展开更多
The reasonable measuring of particle weight and effective sampling of particle state are consid- ered as two important aspects to obtain better estimation precision in particle filter. Aiming at the comprehensive trea...The reasonable measuring of particle weight and effective sampling of particle state are consid- ered as two important aspects to obtain better estimation precision in particle filter. Aiming at the comprehensive treatment of above problems, a novel two-stage prediction and update particle filte- ring algorithm based on particle weight optimization in multi-sensor observation is proposed. Firstly, combined with the construction of muhi-senor observation likelihood function and the weight fusion principle, a new particle weight optimization strategy in multi-sensor observation is presented, and the reliability and stability of particle weight are improved by decreasing weight variance. In addi- tion, according to the prediction and update mechanism of particle filter and unscented Kalman fil- ter, a new realization of particle filter with two-stage prediction and update is given. The filter gain containing the latest observation information is used to directly optimize state estimation in the frame- work, which avoids a large calculation amount and the lack of universality in proposal distribution optimization way. The theoretical analysis and experimental results show the feasibility and efficiency of the proposed algorithm.展开更多
This paper proposes a nonmonotone line search filter method with reduced Hessian updating for solving nonlinear equality constrained optimization.In order to deal with large scale problems,a reduced Hessian matrix is ...This paper proposes a nonmonotone line search filter method with reduced Hessian updating for solving nonlinear equality constrained optimization.In order to deal with large scale problems,a reduced Hessian matrix is approximated by BFGS updates.The new method assures global convergence without using a merit function.By Lagrangian function in the filter and nonmonotone scheme,the authors prove that the method can overcome Maratos effect without using second order correction step so that the locally superlinear convergence is achieved.The primary numerical experiments are reported to show effectiveness of the proposed algorithm.展开更多
Many sensor network applications require location awareness,but it is often too expensive to equip a global positioning system(GPS) receiver for each network node.Hence,localization schemes for sensor networks typical...Many sensor network applications require location awareness,but it is often too expensive to equip a global positioning system(GPS) receiver for each network node.Hence,localization schemes for sensor networks typically use a small number of seed nodes that know their locations and protocols whereby other nodes estimate their locations from the messages they receive.For the inherent shortcomings of general particle filter(the sequential Monte Carlo method) this paper introduces particle swarm optimization and weighted centroid algorithm to optimize it.Based on improvement a distributed localization algorithm named WC-IPF(weighted centroid algorithm improved particle filter) has been proposed for localization.In this localization scheme the initial estimate position can be acquired by weighted centroid algorithm.Then the accurate position can be gotten via improved particle filter recursively.The extend simulation results show that the proposed algorithm is efficient for most condition.展开更多
This paper proposes a filter secant method with nonmonotone line search for non-linearequality constrained optimization.The Hessian of the Lagrangian is approximated using the BFGSsecant update.This new method has mor...This paper proposes a filter secant method with nonmonotone line search for non-linearequality constrained optimization.The Hessian of the Lagrangian is approximated using the BFGSsecant update.This new method has more flexibility for the acceptance of the trial step and requires lesscomputational costs compared with the monotone one.The global and local convergence of the proposedmethod are given under some reasonable conditions.Further,two-step Q-superlinear convergence rateis established by introducing second order correction step.The numerical experiments are reported toshow the effectiveness of the proposed algorithm.展开更多
This paper presents the development of a new nonlinear representation by exploiting the multimodel approach and the new linear representation ARX-Laguerre for each operating region. The resulting multimodel, entitled ...This paper presents the development of a new nonlinear representation by exploiting the multimodel approach and the new linear representation ARX-Laguerre for each operating region. The resulting multimodel, entitled ARX-Laguerre multimodel, is characterized by the parameter number reduction with a recursive representation. However, a significant reduction of this multimodel is subject to an optimal choice of Laguerre poles characterizing each local linear model ARX-Laguerre. Therefore, the authors propose an optimization algorithm to estimate, from input/output measurements, the optimal values of Laguerre poles. The ARX-Laguerre multimodel as well as the proposed optimization algorithm are tested on a continuous stirred tank reactor system （CSTR）. Moreover, the authors take into account a practical validation on an experimental communicating two tank system （CTTS）.展开更多
This paper presents a new nonmonotone filter line search technique in association with the MBFGS method for solving unconstrained minimization.The filter method,which is traditionally used for constrained nonlinear pr...This paper presents a new nonmonotone filter line search technique in association with the MBFGS method for solving unconstrained minimization.The filter method,which is traditionally used for constrained nonlinear programming(NLP),is extended to solve unconstrained NLP by converting the latter to an equality constrained minimization.The nonmonotone idea is employed to the filter method so that the restoration phrase,a common feature of most filter methods,is not needed.The global convergence and fast local convergence rate of the proposed algorithm are established under some reasonable conditions.The results of numerical experiments indicate that the proposed method is efficient.展开更多
基金Project(61072087) supported by the National Natural Science Foundation of ChinaProject(20093048) supported by Shanxi ProvincialGraduate Innovation Fund of China
文摘Perceptual auditory filter banks such as Bark-scale filter bank are widely used as front-end processing in speech recognition systems.However,the problem of the design of optimized filter banks that provide higher accuracy in recognition tasks is still open.Owing to spectral analysis in feature extraction,an adaptive bands filter bank (ABFB) is presented.The design adopts flexible bandwidths and center frequencies for the frequency responses of the filters and utilizes genetic algorithm (GA) to optimize the design parameters.The optimization process is realized by combining the front-end filter bank with the back-end recognition network in the performance evaluation loop.The deployment of ABFB together with zero-crossing peak amplitude (ZCPA) feature as a front process for radial basis function (RBF) system shows significant improvement in robustness compared with the Bark-scale filter bank.In ABFB,several sub-bands are still more concentrated toward lower frequency but their exact locations are determined by the performance rather than the perceptual criteria.For the ease of optimization,only symmetrical bands are considered here,which still provide satisfactory results.
基金supported by the Chinese Natural Science Foundation (61401075)
文摘This paper proposes an estimation method of the directions of arrival(DOA) for the broadband signals received by a uniform planar antenna array including the mutual coupling effect. The process modeling of antenna array receiving dynamic signal is obtained accurately via building the array system electromagnetic space-time model, and the mutual coupling effect is included in the synthesis procedure automatically. The broadband signal is divided into several sub-bands, and the complex weight of these sub-bands frequencies is figured out using the least mean square iteration programming. In the proposed method, the mutual coupling effect is compensated at the different frequencies. The calculation results show that the method is suitable for the uniform linear and uniform circular array pattern integration, and it is commendably satisfied with the requirement of engineering design.
文摘In this paper, the simultaneous perturbation stochastic approximation （SPSA） algorithm is used for seeking optimal parameters in an adaptive filter developed for assimilating observations in the very high dimensional dynamical systems. The main results show that the SPSA is capable of yielding the high filter performance similar to that produced by classical optimization algorithms, with better performance for non-linear filtering problems as more and more observations are assimilated. The advantage of the SPSA is that at each iteration it requires only two measurements of the objective function to approximate the gradient vector regardless of the dimension of the control vector （or maximally, three measurements if second-order optimization algorithms are used）. The SPSA approach is thus free from the need to develop a discrete adjoint of tangent linear model as it is required up to now for solving optimization problems in very high dimensional systems. This technique offers promising perspectives on developing optimal assimilation systems encountered in the field of data assimilation in meteorology and oceanography.
基金Project(20040533035) supported by the National Research Foundation for the Doctoral Program of Higher Education of ChinaProject (60874070) supported by the National Natural Science Foundation of China
文摘To preserve the original signal as much as possible and filter random noises as many as possible in image processing,a threshold optimization-based adaptive template filtering algorithm was proposed.Unlike conventional filters whose template shapes and coefficients were fixed,multi-templates were defined and the right template for each pixel could be matched adaptively based on local image characteristics in the proposed method.The superiority of this method was verified by former results concerning the matching experiment of actual image with the comparison of conventional filtering methods.The adaptive search ability of immune genetic algorithm with the elitist selection and elitist crossover(IGAE) was used to optimize threshold t of the transformation function,and then combined with wavelet transformation to estimate noise variance.Multi-experiments were performed to test the validity of IGAE.The results show that the filtered result of t obtained by IGAE is superior to that of t obtained by other methods,IGAE has a faster convergence speed and a higher computational efficiency compared with the canonical genetic algorithm with the elitism and the immune algorithm with the information entropy and elitism by multi-experiments.
文摘The filter-rods were supplied through compressed air conveyed to cigarette-maker by transmitter in my factory. Usually, each maker has two feed-pipes, it adopts fixed and one-to-one fashion, with the flexible manufacturing system extending, and it＇s original fashion unable to satisfy the needs of a wide range of cigarette brands already, so it cry for a viable and reliable substitute. This paper creatively bring forward the optimized fashion of duct net about filter-rods based on topology structure, it adopts Freud＇s algorithm and improved-separated algorithm in order to achieve the optimized route, it has a apparent effect to improve the transport stability and reduce the transport time of filter- rods.
基金Supported by the National Natural Science Foundations of China(No.61300214,61170243)the Science and Technology Innovation Team Support Plan of Education Department of Henan Province(No.13IRTSTHN021)+2 种基金the Science and Technology Research Key Project of Education Department of Henan Province(No.13A413066)the Basic and Frontier Technology Research Plan of Henan Province(No.132300410148)the Funding Scheme of Young Key Teacher of Henan Province Universities,and the Key Project of Teaching Reform Research of Henan University(No.HDXJJG2013-07)
文摘The reasonable measuring of particle weight and effective sampling of particle state are consid- ered as two important aspects to obtain better estimation precision in particle filter. Aiming at the comprehensive treatment of above problems, a novel two-stage prediction and update particle filte- ring algorithm based on particle weight optimization in multi-sensor observation is proposed. Firstly, combined with the construction of muhi-senor observation likelihood function and the weight fusion principle, a new particle weight optimization strategy in multi-sensor observation is presented, and the reliability and stability of particle weight are improved by decreasing weight variance. In addi- tion, according to the prediction and update mechanism of particle filter and unscented Kalman fil- ter, a new realization of particle filter with two-stage prediction and update is given. The filter gain containing the latest observation information is used to directly optimize state estimation in the frame- work, which avoids a large calculation amount and the lack of universality in proposal distribution optimization way. The theoretical analysis and experimental results show the feasibility and efficiency of the proposed algorithm.
基金supported by the National Science Foundation of China under Grant No.10871130the Ph.D Foundation under Grant No.20093127110005+1 种基金the Shanghai Leading Academic Discipline Project under Grant No.S30405the Innovation Program of Shanghai Municipal Education Commission under Grant No.12YZ174
文摘This paper proposes a nonmonotone line search filter method with reduced Hessian updating for solving nonlinear equality constrained optimization.In order to deal with large scale problems,a reduced Hessian matrix is approximated by BFGS updates.The new method assures global convergence without using a merit function.By Lagrangian function in the filter and nonmonotone scheme,the authors prove that the method can overcome Maratos effect without using second order correction step so that the locally superlinear convergence is achieved.The primary numerical experiments are reported to show effectiveness of the proposed algorithm.
文摘Many sensor network applications require location awareness,but it is often too expensive to equip a global positioning system(GPS) receiver for each network node.Hence,localization schemes for sensor networks typically use a small number of seed nodes that know their locations and protocols whereby other nodes estimate their locations from the messages they receive.For the inherent shortcomings of general particle filter(the sequential Monte Carlo method) this paper introduces particle swarm optimization and weighted centroid algorithm to optimize it.Based on improvement a distributed localization algorithm named WC-IPF(weighted centroid algorithm improved particle filter) has been proposed for localization.In this localization scheme the initial estimate position can be acquired by weighted centroid algorithm.Then the accurate position can be gotten via improved particle filter recursively.The extend simulation results show that the proposed algorithm is efficient for most condition.
基金supported by the National Science Foundation of China under Grant No. 10871130the Ph.D. Foundation under Grant No. 20093127110005+1 种基金the Shanghai Leading Academic Discipline Project under Grant No. S30405the Shanghai Finance Budget Project under Grant Nos. 1139IA0013 and 1130IA15
文摘This paper proposes a filter secant method with nonmonotone line search for non-linearequality constrained optimization.The Hessian of the Lagrangian is approximated using the BFGSsecant update.This new method has more flexibility for the acceptance of the trial step and requires lesscomputational costs compared with the monotone one.The global and local convergence of the proposedmethod are given under some reasonable conditions.Further,two-step Q-superlinear convergence rateis established by introducing second order correction step.The numerical experiments are reported toshow the effectiveness of the proposed algorithm.
文摘This paper presents the development of a new nonlinear representation by exploiting the multimodel approach and the new linear representation ARX-Laguerre for each operating region. The resulting multimodel, entitled ARX-Laguerre multimodel, is characterized by the parameter number reduction with a recursive representation. However, a significant reduction of this multimodel is subject to an optimal choice of Laguerre poles characterizing each local linear model ARX-Laguerre. Therefore, the authors propose an optimization algorithm to estimate, from input/output measurements, the optimal values of Laguerre poles. The ARX-Laguerre multimodel as well as the proposed optimization algorithm are tested on a continuous stirred tank reactor system （CSTR）. Moreover, the authors take into account a practical validation on an experimental communicating two tank system （CTTS）.
基金supported by the National Science Foundation under Grant No.11371253the Science Foundation under Grant No.11C0336 of Provincial Education Department of Hunan
文摘This paper presents a new nonmonotone filter line search technique in association with the MBFGS method for solving unconstrained minimization.The filter method,which is traditionally used for constrained nonlinear programming(NLP),is extended to solve unconstrained NLP by converting the latter to an equality constrained minimization.The nonmonotone idea is employed to the filter method so that the restoration phrase,a common feature of most filter methods,is not needed.The global convergence and fast local convergence rate of the proposed algorithm are established under some reasonable conditions.The results of numerical experiments indicate that the proposed method is efficient.
