DocumentCode
2290582
Title
An analog implementation of radial basis neural networks (RBNN) using BiCMOS technology
Author
de Oliveira, J.P. ; Oki, N.
Author_Institution
Departamento de Engenharia Eletrica, Univ. Estadual Paulista, Ilha Solteira, Brazil
Volume
2
fYear
2001
fDate
2001
Firstpage
705
Abstract
This paper describes an 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) are changed with a programmable current source. Results obtained with PSPICE software are shown
Keywords
BiCMOS analogue integrated circuits; Gaussian distribution; SPICE; VLSI; analogue processing circuits; circuit simulation; neural chips; radial basis function networks; BiCMOS technology; Gaussian function; PSPICE software; analog implementation; bipolar differential pair; programmable current source; radial basis neural networks; Analog circuits; Arithmetic; BiCMOS integrated circuits; Circuit testing; Gaussian approximation; Neural networks; Operational amplifiers; SPICE; Transconductance; Very large scale integration;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2001. MWSCAS 2001. Proceedings of the 44th IEEE 2001 Midwest Symposium on
Conference_Location
Dayton, OH
Print_ISBN
0-7803-7150-X
Type
conf
DOI
10.1109/MWSCAS.2001.986285
Filename
986285
Link To Document