Realization of the Conscience Mechanism in CMOS Implementation of Winner-Takes-All Self-Organizing Neural Networks

This paper presents a complementary metal–oxide– semiconductor (CMOS) implementation of a conscience mechanism used to improve the effectiveness of learning in the winnertakes- all (WTA) artificial neural networks (ANNs) realized at the transistor level. This mechanism makes it possible to eliminate the effect of the so-called “dead neurons,” which do not take part in the learning phase competition. These neurons usually have a detrimental effect on the network performance, increasing the quantization error. The proposed mechanism comes as part of the analog implementation of the WTA neural networks (NNs) designed for applications to ultralow power portable diagnostic devices for online analysis of ECGbiomedical signals. The study presents Matlab simulations of the network’s model, discusses postlayout circuit level simulations and includes results of measurement completed for the physical realization of the circuit.


Published in:
IEEE Transactions on Neural Networks, 21, 6, 961-971
Year:
2010
Publisher:
Institute of Electrical and Electronics Engineers
ISSN:
1045-9227
Keywords:
Laboratories:


Note: The status of this file is: EPFL only


 Record created 2011-02-14, last modified 2018-03-17

n/a:
Download fulltext
PDF

Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)