A Beta basis function neural network in CMOS subthreshold mode

被引：2
|
作者：
Samet, M
Masmoudi, M
Alimi, AM
机构：
[1] Univ Sfax, Natl Sch Engineers Sfax, Dept Elect Engn, LETI Lab Elect & Informat Technol, Sfax 3038, Tunisia
[2] Univ Sfax, Natl Sch Engineers Sfax, Dept Elect Engn, REGIM Res Grp Intelligent Machines, Sfax 3038, Tunisia
来源：
INTERNATIONAL JOURNAL OF ELECTRONICS | 2001年 / 88卷 / 06期
关键词：
D O I：
10.1080/00207210110041489
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Beta basis function neural networks (BBFNNs) are powerful systems for learning and universal approximation. In this paper, we present a hardware implementation of the Beta neuron using the CMOS subthreshold mode. We describe the low power-low voltage analogue Beta neuron circuit. Three main modules are used to realize the electronic Beta function: a logarithmic current-to-voltage converter, a multiplier and an exponential voltage-to-current converter. Simulation results show the validity of our neural hardware implementation. The parameters of the electronic Beta function are controlled independently by current sources. This analogue implementation could be used easily to realize analogue BBFNNs.
引用
收藏
页码：645 / 657
页数：13
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