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TOBEŠ, Z., RAIDA, Z.
Original Title
Improvements of Analog Neural Networks Based on Kalman Filter
Type
journal article - other
Language
English
Original 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
Authors
RIV year
2002
Released
1. 4. 2002
ISBN
1210-2512
Periodical
Radioengineering
Year of study
11
Number
3
State
Czech Republic
Pages from
6
Pages to
13
Pages count
8
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" }