title: Realization of the conscience mechanism in CMOS implementation of winner-takes-all self-organizing neural networks.
abstract: This paper presents a complementary metal-oxide-semiconductor (CMOS) implementation of a conscience mechanism used to improve the effectiveness of learning in the winner-takes-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 ECG biomedical 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.
authors.affiliation: Institute of Microtechnology, Swiss Federal Institute of Technology, Lausanne, CH-2000 Neuchâtel, Switzerland. rafal.dlugosz@epfl.ch
authors.forename: Rafa
authors.initials: R
authors.lastname: Dlugosz
authors.forename: Tomasz
authors.initials: T
authors.lastname: Talaska
authors.forename: Witold
authors.initials: W
authors.lastname: Pedrycz
authors.forename: Ryszard
authors.initials: R
authors.lastname: Wojtyna
mesh_terms: D003198:Computer Simulation; D003242:Conscience; D005716:Game Theory; D006801:Humans; D007858:Learning / Q000502:physiology*; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D014173:Transistors, Electronic