Scholarly Works

Nonlinear state estimation using neural filters

Nonlinear state estimation using neural filters

Abstract

In this paper we present procedures for estimating the state of a nonlinear dynamical system, which are based on the use of radial basis function (RBF) networks. Experimental results ore presented, which compare the performance of this approach with that of J.T. Lo (1995).

Authors

Haykin S; Yee P

Volume

1

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Publication Date

January 1, 1997

DOI

10.1109/acssc.1996.600935

Name of conference

Conference Record of The Thirtieth Asilomar Conference on Signals, Systems and Computers

Conference proceedings

2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)

ISSN

1058-6393

Associated Experts

Simon Haykin

Professor Emeritus, Faculty of Engineering

Labels

Fields of Research (FoR)

46 Information and Computing Sciences 40 Engineering 4611 Machine Learning

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