DocumentCode
423643
Title
Properties of a chaotic network separating memory patterns
Author
Matykiewicz, Pawel
Author_Institution
Dept. of Inf., Nicholas Copernicus Univ., Torun, Poland
Volume
2
fYear
2004
fDate
25-29 July 2004
Firstpage
931
Abstract
A simple method aimed at improving the separation abilities of a chaotic neural network is presented and its memory properties investigated. Estimation of the invulnerability to the external input disturbance and the damage of weight connections are performed. Significant improvements of retrieval characteristic are reported. When weight connections are damaged, high instability of separation of the memory patterns is observed.
Keywords
chaos; content-addressable storage; neural nets; pattern classification; chaotic neural network; content-addressable storage; external input disturbance; memory pattern separation; weight connection damages; Associative memory; Chaos; Distortion measurement; Electronic mail; Equations; Informatics; Information representation; Neural networks; Neurons; Object recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
ISSN
1098-7576
Print_ISBN
0-7803-8359-1
Type
conf
DOI
10.1109/IJCNN.2004.1380055
Filename
1380055
Link To Document