DocumentCode :
1093525
Title :
Application of the CMAC input encoding scheme in the N-tuple approximation network
Author :
Kolcz, A. ; Allinson, N.M.
Author_Institution :
Dept. of Electron., York Univ., UK
Volume :
141
Issue :
3
fYear :
1994
fDate :
5/1/1994 12:00:00 AM
Firstpage :
177
Lastpage :
183
Abstract :
The N-tuple approximation network offers many advantages over conventional neural networks in terms of speed of operation and its ability to realise arbitrary nonlinear mappings. However, its generalisation/selectivity properties depend strongly on the form of input encoding being used in the system. The paper analyses the suitability of use of the CMAC code for the N-tuple networks, and compares its properties with existing schemes. It is argued that the application of this type of encoding can provide desirable monotonic mapping between input and pattern space distances without the penalty of very long binary patterns as is the case for bar-chart encoding. Additionally, similarities between the classic N-tuple and CMAC networks are highlighted
Keywords :
codes; encoding; learning (artificial intelligence); neural nets; pattern recognition; CMAC; N-tuple approximation network; N-tuple networks; arbitrary nonlinear mappings; bar-chart encoding; generalisation; input encoding scheme; monotonic mapping; neural networks; pattern space distance; selectivity; supervised neural network; very long binary patterns;
fLanguage :
English
Journal_Title :
Computers and Digital Techniques, IEE Proceedings -
Publisher :
iet
ISSN :
1350-2387
Type :
jour
DOI :
10.1049/ip-cdt:19941004
Filename :
287060
Link To Document :
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