Analysis of stochastic gradient identification of polynomial nonlinear systems with memory

被引：0

作者：

Celka, P ^{[1
]}

Bershad, NJ ^{[1
]}

Vesin, JM ^{[1
]}

机构：

[1] Swiss Fed Inst Technol, Dept Elect Engn, Signal Proc Lab, Zurich, Switzerland

来源：

ICASSP '99: 1999 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, PROCEEDINGS VOLS I-VI | 1999年

关键词：

D O I：

10.1109/ICASSP.1999.756216

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

This paper present analytical, numerical and experimental results for a stochastic gradient adaptive scheme which identifies a polynomial-type nonlinear system with memory for noisy output observations. The analysis includes the computation of the stationary points, the mean square error surface, and the mean behavior of the algorithm for Gaussian data. Monte Carlo simulations confirm the theoretical predictions which show a small sensitivity to the observation noise.

引用

页码：1293 / 1296

页数：4

共 50 条

[1] Analysis of stochastic gradient identification of polynomial nonlinear systems with memory
Celka, P.
Bershad, N.J.
Vesin, J.M.
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 1999, 3 : 1293 - 1296
[2] Stochastic analysis of gradient adaptive identification of nonlinear systems with memory
Bershad, NJ
Celka, P
Vesin, JM
PROCEEDINGS OF THE 1998 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-6, 1998, : 1421 - 1424
[3] Fluctuation analysis of stochastic gradient identification of polynomial Wiener systems
Celka, P
Bershad, NJ
Vesin, JM
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2000, 48 (06) : 1820 - 1825
[4] Stochastic gradient identification of polynomial Wiener systems: Analysis and application
Celka, P
Bershad, NJ
Vesin, JM
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2001, 49 (02) : 301 - 313
[5] Stochastic analysis of gradient adaptive identification of nonlinear systems with memory for Gaussian data and noisy input and output measurements
Bershad, NJ
Celka, P
Vesin, JM
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1999, 47 (03) : 675 - 689
[6] Analysis of stochastic gradient identification of Wiener-Hammerstein systems for nonlinearities with hermite polynomial expansions
Bershad, NJ
Celka, P
McLaughlin, S
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2001, 49 (05) : 1060 - 1072
[7] Stochastic gradient identification algorithm and its convergence for feedback nonlinear systems
Wei C.
Xu L.
Ding F.
Kongzhi Lilun Yu Yingyong/Control Theory and Applications, 2023, 40 (10): : 1757 - 1764
[8] Polynomial filtering and identification of discrete-time nonlinear uncertain stochastic systems
Germani, Alfredo
Manes, Costanzo
Palumbo, Pasquale
2005 44TH IEEE CONFERENCE ON DECISION AND CONTROL & EUROPEAN CONTROL CONFERENCE, VOLS 1-8, 2005, : 1917 - 1922
[9] Analysis of stochastic gradient tracking of time-varying polynomial Wiener systems
Bershad, NJ
Celka, P
Vesin, JM
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2000, 48 (06) : 1676 - 1686
[10] POLYNOMIAL APPROXIMATIONS TO MOMENTS OF NONLINEAR STOCHASTIC SYSTEMS
NISHIYAMA, K
JOURNAL OF THE PHYSICAL SOCIETY OF JAPAN, 1975, 39 (05) : 1166 - 1168

← 1 2 3 4 5 →