Optimum nonlinear filtering

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 1997Publisher:Institute of Electrical and Electronics Engineers (IEEE)Journal:IEEE Transactions on Signal Processing, volume 45, pages 2,774-2,786 (issn: 1053-587X,

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Authors: Simon Haykin 0001; Paul Yee; Eric Derbez;

doi: 10.1109/78.650104

Optimum nonlinear filtering

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Abstract

This paper is composed of two parts. The first part surveys the literature regarding optimum nonlinear filtering from the (continuous-time) stochastic analysis point of view, and the other part explores the impact of recent applications of neural networks (in a discrete-time context) to nonlinear filtering. In particular, the results obtained by using a regularized form of radial basis function (RBF) networks are presented in fair detail.

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