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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/66666
Title: 
An analog implementation of radial basis neural networks (RBNN) using BiCMOS technology
Author(s): 
Institution: 
Universidade Estadual Paulista (UNESP)
Abstract: 
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.
Issue Date: 
1-Dec-2001
Citation: 
Midwest Symposium on Circuits and Systems, v. 2, p. 705-708.
Time Duration: 
705-708
Keywords: 
  • 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
Source: 
http://dx.doi.org/10.1109/MWSCAS.2001.986285
URI: 
Access Rights: 
Acesso restrito
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/66666
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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