A new recursive algorithm of multi variable time varying AR model is proposed. By changing the form of AR model, the parameter estimation can be regarded as state estimation of state equations. Then the Kalman filte...A new recursive algorithm of multi variable time varying AR model is proposed. By changing the form of AR model, the parameter estimation can be regarded as state estimation of state equations. Then the Kalman filter is used to estimate the variation of展开更多
In this article, the problem on the estimation of the convolution model parameters is considered. The recursive algorithm for estimating model parameters is introduced from the orthogonal procedure of the data, the co...In this article, the problem on the estimation of the convolution model parameters is considered. The recursive algorithm for estimating model parameters is introduced from the orthogonal procedure of the data, the convergence of this algorithm is theoretically discussed, and a sufficient condition for the convergence criterion of the orthogonal procedure is given. According to this condition, the recursive algorithm is convergent to model wavelet A- = （1, α1,..., αq）.展开更多
Order-recursive least-squares(ORLS)algorithms are applied to the prob-lems of estimation and identification of FIR or ARMA system parameters where a fixedset of input signal samples is available and the desired order ...Order-recursive least-squares(ORLS)algorithms are applied to the prob-lems of estimation and identification of FIR or ARMA system parameters where a fixedset of input signal samples is available and the desired order of the underlying model isunknown.On the basis of several universal formulae for updating nonsymmetric projec-tion operators,this paper presents three kinds of LS algorithms,called nonsymmetric,symmetric and square root normalized fast ORLS algorithms,respectively.As to the au-thors’ knowledge,the first and the third have not been so far provided,and the second isone of those which have the lowest computational requirement.Several simplified versionsof the algorithms are also considered.展开更多
Based on the idea of the set-membership identification, a modified recursive least squares algorithm with variable gain, variable forgetting factor and resetting is presented. The concept of the error tolerance level ...Based on the idea of the set-membership identification, a modified recursive least squares algorithm with variable gain, variable forgetting factor and resetting is presented. The concept of the error tolerance level is proposed. The selection criteria of the error tolerance level are also given according to the min-max principle. The algorithm is particularly suitable for tracing time-varying systems and is similar in computational complexity to the standard recursive least squares algorithm. The superior performance of the algorithm is verified ma simulation studies on a dynamic fermentation process.展开更多
Householder transform is used to triangularize the data matrix, which is basedon the near prediction error equation. It is proved that the sum of squared residuals for eachAR order can be obtained by the main diagonal...Householder transform is used to triangularize the data matrix, which is basedon the near prediction error equation. It is proved that the sum of squared residuals for eachAR order can be obtained by the main diagonal elements of upper triangular matrix, so thecolumn by column procedure can be used to develop a recursive algorithm for AR modeling andspectral estimation. In most cases, the present algorithm yields the same results as the covariancemethod or modified covariance method does. But in some special cases where the numerical ill-conditioned problems are so serious that the covariance method and modified covariance methodfail to estimate AR spectrum, the presented algorithm still tends to keep good performance. Thetypical computational results are presented finally.展开更多
This paper proposes a recursive least squares algorithm for a nonlinear additive system with time delay.By the Weierstrass approximation theorem and the key term separation principle, the model can be simplified as an...This paper proposes a recursive least squares algorithm for a nonlinear additive system with time delay.By the Weierstrass approximation theorem and the key term separation principle, the model can be simplified as an identification model. Based on the identification model, a recursive least squares identification algorithm is used to estimate all the unknown parameters of the time-delayed additive system. An example is provided to show the effectiveness of the proposed algorithm.展开更多
This paper summarizes the parameter estimation of systems with set-valued signals, which can be classified to three catalogs: one-time completed algorithms, iterative methods and recursive algorithms. For one-time com...This paper summarizes the parameter estimation of systems with set-valued signals, which can be classified to three catalogs: one-time completed algorithms, iterative methods and recursive algorithms. For one-time completed algorithms, empirical measure method is one of the earliest methods to estimate parameters by using set-valued signals, which has been applied to the adaptive tracking of periodic target signals. The iterative methods seek numerical solutions of the maximum likelihood estimation, which have been applied to both complex diseases diagnosis and radar target recognition. The recursive algorithms are constructed via stochastic approximation and stochastic gradient methods, which have been applied to adaptive tracking of non-periodic signals.展开更多
提出了一种基于改进三次相位函数的多分量线性调频(linear frequency modulation,LFM)信号参数估计算法。该算法只需要通过二阶非线性变换在信号参数空间形成最大值来估计LFM信号参数。在多分量的情况下,讨论了信号自项和交叉项与时间...提出了一种基于改进三次相位函数的多分量线性调频(linear frequency modulation,LFM)信号参数估计算法。该算法只需要通过二阶非线性变换在信号参数空间形成最大值来估计LFM信号参数。在多分量的情况下,讨论了信号自项和交叉项与时间的关系,发现自项和交叉项对时间有不同的依赖性。为了克服交叉项的影响,提出了加权平均的方法来改进算法。然后推导了三次相位函数的FFT快速算法,并进一步采用了舍入最近采样点的方法改进算法,使其可以应用于实际的离散采样系统。仿真试验表明,此方法在低信噪比下估计多分量LFM信号参数效果显著,其快速算法在大大降低运算量的同时,与原算法相比较,仍然保持了良好的估计性能。展开更多
文摘A new recursive algorithm of multi variable time varying AR model is proposed. By changing the form of AR model, the parameter estimation can be regarded as state estimation of state equations. Then the Kalman filter is used to estimate the variation of
基金Project supported by Scientific Research Fund of Chongqing Municipal Education Commission (kj0604-16)
文摘In this article, the problem on the estimation of the convolution model parameters is considered. The recursive algorithm for estimating model parameters is introduced from the orthogonal procedure of the data, the convergence of this algorithm is theoretically discussed, and a sufficient condition for the convergence criterion of the orthogonal procedure is given. According to this condition, the recursive algorithm is convergent to model wavelet A- = （1, α1,..., αq）.
文摘Order-recursive least-squares(ORLS)algorithms are applied to the prob-lems of estimation and identification of FIR or ARMA system parameters where a fixedset of input signal samples is available and the desired order of the underlying model isunknown.On the basis of several universal formulae for updating nonsymmetric projec-tion operators,this paper presents three kinds of LS algorithms,called nonsymmetric,symmetric and square root normalized fast ORLS algorithms,respectively.As to the au-thors’ knowledge,the first and the third have not been so far provided,and the second isone of those which have the lowest computational requirement.Several simplified versionsof the algorithms are also considered.
文摘Based on the idea of the set-membership identification, a modified recursive least squares algorithm with variable gain, variable forgetting factor and resetting is presented. The concept of the error tolerance level is proposed. The selection criteria of the error tolerance level are also given according to the min-max principle. The algorithm is particularly suitable for tracing time-varying systems and is similar in computational complexity to the standard recursive least squares algorithm. The superior performance of the algorithm is verified ma simulation studies on a dynamic fermentation process.
文摘Householder transform is used to triangularize the data matrix, which is basedon the near prediction error equation. It is proved that the sum of squared residuals for eachAR order can be obtained by the main diagonal elements of upper triangular matrix, so thecolumn by column procedure can be used to develop a recursive algorithm for AR modeling andspectral estimation. In most cases, the present algorithm yields the same results as the covariancemethod or modified covariance method does. But in some special cases where the numerical ill-conditioned problems are so serious that the covariance method and modified covariance methodfail to estimate AR spectrum, the presented algorithm still tends to keep good performance. Thetypical computational results are presented finally.
基金the National Natural Science Foundation of China(No.61403165)the Natural Science Foundation of Jiangsu Province(Nos.BK20131109 and BK20141115)+1 种基金the Project of Philosophy and Social Science Research in Colleges and Universities in Jiangsu Province(No.2014SJD381)the Post Doctoral Foundation of Jiangsu Province(No.1501015A)
文摘This paper proposes a recursive least squares algorithm for a nonlinear additive system with time delay.By the Weierstrass approximation theorem and the key term separation principle, the model can be simplified as an identification model. Based on the identification model, a recursive least squares identification algorithm is used to estimate all the unknown parameters of the time-delayed additive system. An example is provided to show the effectiveness of the proposed algorithm.
基金Supported by the National Natural Science Foundation of China(Nos.61803370,61622309)the China Postdoctoral Science Foundation(No.2018M630216)the National Key Research and Development Program of China(No.2016YFB0901902)
文摘This paper summarizes the parameter estimation of systems with set-valued signals, which can be classified to three catalogs: one-time completed algorithms, iterative methods and recursive algorithms. For one-time completed algorithms, empirical measure method is one of the earliest methods to estimate parameters by using set-valued signals, which has been applied to the adaptive tracking of periodic target signals. The iterative methods seek numerical solutions of the maximum likelihood estimation, which have been applied to both complex diseases diagnosis and radar target recognition. The recursive algorithms are constructed via stochastic approximation and stochastic gradient methods, which have been applied to adaptive tracking of non-periodic signals.
文摘提出了一种基于改进三次相位函数的多分量线性调频(linear frequency modulation,LFM)信号参数估计算法。该算法只需要通过二阶非线性变换在信号参数空间形成最大值来估计LFM信号参数。在多分量的情况下,讨论了信号自项和交叉项与时间的关系,发现自项和交叉项对时间有不同的依赖性。为了克服交叉项的影响,提出了加权平均的方法来改进算法。然后推导了三次相位函数的FFT快速算法,并进一步采用了舍入最近采样点的方法改进算法,使其可以应用于实际的离散采样系统。仿真试验表明,此方法在低信噪比下估计多分量LFM信号参数效果显著,其快速算法在大大降低运算量的同时,与原算法相比较,仍然保持了良好的估计性能。
