Result Details

Improvements of Analog Neural Networks Based on Kalman Filter

TOBEŠ, Z., RAIDA, Z. Improvements of Analog Neural Networks Based on Kalman Filter. Radioengineering, 2002, vol. 11, no. 3, 8 p. ISSN: 1210-2512.

Type

journal article

Language

English

Authors

Tobeš Zdeněk, Ing.
Raida Zbyněk, prof. Dr. Ing.

Abstract

In the paper, original improvements of recurrent analog neural networks, which are based on Kalman filter, are presented. These improvements eliminate some disadvantages of the classical Kalman neural network and enable a real time processing of quickly changing signals, which appear in adaptive antennas and similar applications. This goal is reached using such circuit elements, which increase the convergence rate of the network and decrease the dependence of convergence rate on the ratio of eigenvalues of the correlation matrix of input signals.

Keywords

Kalman filter, analog recurrent neural networks, convergence rate, stability

Published

2002

Pages

Journal

Radioengineering, vol. 11, no. 3, ISSN 1210-2512

BibTeX

@article{BUT40903,
  author="Zdeněk {Tobeš} and Zbyněk {Raida}",
  title="Improvements of Analog Neural Networks Based on Kalman Filter",
  journal="Radioengineering",
  year="2002",
  volume="11",
  number="3",
  pages="8",
  issn="1210-2512"
}

Departments

Department of Radio Electronics (UREL)