Analogue Globally Stable WTA Neural Circuit

Author

Tymoshchuk, Pavlo ; Lobur, Mykhaylo

Author_Institution

Dept. of CAD/CAM, Lviv Polytech. Nat. Univ.

fYear

2006

fDate

24-27 May 2006

Firstpage

19

Lastpage

23

Abstract

A new inhibitory analogue WTA (winner-take-all) neural circuit which identifies maximal among N unknown input signals is proposed. As a building block the second order analogue globally stable neural network of Hopfield type is used. The connection matrix belongs to the class of diagonally stable block diagonal matrices and the activation functions are piecewise linear or sigmoid. The mathematical justification of the circuit functioning, comparative evaluation with analogs and computer simulation results are given

Keywords

Hopfield neural nets; continuous time systems; transfer functions; Hopfield type; analogue winner-take-all neural circuit; block diagonal matrix; circuit functioning; computer simulation; linear activation function; sigmoid activation function; Circuits; Computer simulation; Convergence; Hopfield neural networks; Neural networks; Neurons; Pattern classification; Pattern recognition; Piecewise linear techniques; Signal processing; Inhibitory analogue WTA neural circuit; computer simulation results; diagonally stable block diagonal matrix; sigmoid activation function;

fLanguage

English

Publisher

ieee

Conference_Titel

Perspective Technologies and Methods in MEMS Design, 2006. MEMSTECH 2006. Proceedings of the 2nd International Conference on

Conference_Location

Lviv

Print_ISBN

966-553-517-X

Type

conf

DOI

10.1109/MEMSTECH.2006.288654

Filename

4068418