Detail publikace

Improvements of Analog Neural Networks Based on Kalman Filter

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

TOBEŠ, Z., RAIDA, Z.

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"
}