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 are presented, which compare the performance of this approach with that of J.T. Lo published in 1995.

Authors

Haykin S; Yee P

Volume

2

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Publication Date

January 1, 1996

DOI

10.1109/milcom.1996.569416

Name of conference

Proceedings of MILCOM '96 IEEE Military Communications Conference

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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