DocumentCode
296146
Title
Quick learning for multidirectional associative memories
Author
Hattori, Motonobu ; Hagiwara, Masafumi
Author_Institution
Dept. of Electr. Eng., Keio Univ., Yokohama, Japan
Volume
4
fYear
1995
fDate
Nov/Dec 1995
Firstpage
1949
Abstract
In this paper, a quick learning algorithm for multidirectional associative memories (MAMs) is proposed. With this quick learning algorithm, not only the storage capacity of the MAMs can be improved, but also the recall of all training data can be guaranteed. In addition, several important characteristics of the MAMs such as the relation between the required learning epochs and the number of layers, and the relation between the noise reduction effect and the number of layers are introduced
Keywords
Hebbian learning; associative processing; content-addressable storage; neural nets; Hebbian learning; multidirectional associative memories; neural networks; noise reduction effect; quick learning algorithm; storage capacity; Associative memory; Hebbian theory; Humans; Image coding; Magnesium compounds; Noise reduction; Parallel processing; Psychology; Reverberation; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2768-3
Type
conf
DOI
10.1109/ICNN.1995.488969
Filename
488969
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