DocumentCode
3294772
Title
Extension of cellular automata to neural computation: theory and applications
Author
Blayo, François ; Marchal, Pierre
Author_Institution
Microcomput. Lab., Swiss Fed. Inst. of Lausanne, Switzerland
fYear
1989
fDate
0-0 1989
Firstpage
197
Abstract
A relationship between cellular automata and neuro-mimetic theory is presented. A systolic approach is proposed for evaluating a first-neighborhood cellular automaton. This method has been extended for a full-neighborhood automaton and applied to Hopfield-like neural networks. Three possible resulting solutions are discussed, and a new approach which allows for full extensibility is shown. Appropriate external storage of the parameters provides a flexible recognition system able to dynamically modify the synaptic weights. Such a function will be used later for the implementation of an autoadaptive system.<>
Keywords
finite automata; neural nets; parallel architectures; Hopfield-like neural networks; autoadaptive system; cellular automata; dual ring array architecture; external parameters storage; first neighbourhood automaton; flexible recognition system; full-neighborhood automaton; neural computation; neuro-mimetic theory; synaptic weights; systolic architectures; Finite automata; Neural networks; Parallel architectures;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1989. IJCNN., International Joint Conference on
Conference_Location
Washington, DC, USA
Type
conf
DOI
10.1109/IJCNN.1989.118699
Filename
118699
Link To Document