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Detail publikace
TOBEŠ, Z., RAIDA, Z.
Originální název
Improvements of Analog Neural Networks Based on Kalman Filter
Typ
článek v časopise - ostatní, Jost
Jazyk
angličtina
Originální abstrakt
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.
Klíčová slova
Kalman filter, analog recurrent neural networks, convergence rate, stability
Autoři
Rok RIV
2002
Vydáno
1. 4. 2002
ISSN
1210-2512
Periodikum
Radioengineering
Ročník
11
Číslo
3
Stát
Česká republika
Strany od
6
Strany do
13
Strany počet
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" }