DocumentCode
288353
Title
A large scale neural network with nonlinear synapses
Author
Lont, Jerzy B.
Author_Institution
Electron. Lab., Swiss Federal Inst. of Technol., Zurich, Switzerland
Volume
1
fYear
1994
fDate
27 Jun-2 Jul 1994
Firstpage
350
Abstract
In this paper, we prove the usefulness of multi-layer perceptrons with nonlinear synapses for real-size applications such as handwritten character recognition. We describe some simulations of a large scale neural network with nonlinear synapses. The convergence speed is shown to be better than for the networks with linear multipliers. Some issues concerning the VLSI implementation are discussed
Keywords
VLSI; character recognition; multilayer perceptrons; VLSI implementation; convergence speed; handwritten character recognition; large scale neural network; multilayer perceptrons; nonlinear synapses; real-size applications; CMOS technology; Character recognition; Laboratories; Large-scale systems; Multilayer perceptrons; Neural networks; Neurons; Physics; Very large scale integration; Wires;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-1901-X
Type
conf
DOI
10.1109/ICNN.1994.374188
Filename
374188
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