An analog implementation of radial basis neural networks (RBNN) using BiCMOS technology
| Contribuinte(s) |
Universidade Estadual Paulista (UNESP) |
|---|---|
| Data(s) |
27/05/2014
27/05/2014
01/12/2001
|
| 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. |
| Formato |
705-708 |
| Identificador |
http://dx.doi.org/10.1109/MWSCAS.2001.986285 Midwest Symposium on Circuits and Systems, v. 2, p. 705-708. http://hdl.handle.net/11449/66666 10.1109/MWSCAS.2001.986285 WOS:000175971700158 2-s2.0-0035575292 |
| Idioma(s) |
eng |
| Relação |
Midwest Symposium on Circuits and Systems |
| Direitos |
closedAccess |
| 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 |
| Tipo |
info:eu-repo/semantics/conferencePaper |
