An analog implementation of radial basis neural networks (RBNN) using BiCMOS technology

Fontes externas

http://dx.doi.org/10.1109/MWSCAS.2001.986285

Fontes externas

http://dx.doi.org/10.1109/MWSCAS.2001.986285

Data

Autores

De Oliveira, J. P.

Editor

Institute of Electrical and Electronics Engineers (IEEE)

Tipo

Trabalho apresentado em evento

Direito de acesso

Acesso aberto

Fontes externas

http://dx.doi.org/10.1109/MWSCAS.2001.986285

Fontes externas

http://dx.doi.org/10.1109/MWSCAS.2001.986285

Resumo

This paper describes a analog implementation of radial basis neural networks (RBNN) in BiCMOS technology. The RBNN uses a gaussian function obtained through the characteristic of the bipolar differential pair. The gaussian parameters (gain, center and width) is changed with programmable current source. Results obtained with PSPICE software is showed.

Palavras-chave

CMOS integrated circuits , Computer software , Electric currents , Gain measurement , Neural networks , Numerical methods , VLSI circuits , BiCMOS technology , Gaussian function , Programmable current source , Radial basis neural networks , Integrated circuit manufacture

Idioma

Inglês

Citação

Midwest Symposium on Circuits and Systems, v. 2, p. 705-708.

URI

http://hdl.handle.net/11449/66666

Coleções

Ilha Solteira - FEIS - Faculdade de Engenharia

Unidades

Unidade

Ilha Solteira, Faculdade de Engenharia - FEIS

FEIS

Campus: Ilha Solteira

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