DocumentCode
350947
Title
Associative memory of gray-scale images based on chaotic neural networks
Author
Li, Ke ; Yang, Luxi ; Liu, Ju ; He, Zhenya
Author_Institution
Dept. of Radio Eng., Southeast Univ., Nanjing, China
Volume
2
fYear
1999
fDate
36495
Firstpage
1375
Abstract
We propose a novel correlative learning rule for multi-value patterns, considering that conventional associative memory system processes only binary ones. Successful memory and recognition were achieved on the bases of a modified globally coupled map model (S-GCM) with the proposed method. An analysis of the recognition results and factors are also given
Keywords
chaos; content-addressable storage; image recognition; learning (artificial intelligence); neural nets; associative memory system; chaotic neural networks; correlative learning rule; gray-scale images; image recognition results; modified globally coupled map model; multi-value patterns; Associative memory; Chaos; Cognition; Electronic mail; Gray-scale; Helium; Neural networks; Olfactory; Rabbits; Spatiotemporal phenomena;
fLanguage
English
Publisher
ieee
Conference_Titel
TENCON 99. Proceedings of the IEEE Region 10 Conference
Conference_Location
Cheju Island
Print_ISBN
0-7803-5739-6
Type
conf
DOI
10.1109/TENCON.1999.818686
Filename
818686
Link To Document