DocumentCode
922487
Title
A neuron-weighted learning algorithm and its hardware implementation in associative memories
Author
Wang, Tao ; Zhuang, Xinhau ; Xing, Xiaoliang ; Xiao, Xipeng
Author_Institution
Dept. of Comput. Sci. & Eng., Zhejiang Univ., Hangzhou, China
Volume
42
Issue
5
fYear
1993
fDate
5/1/1993 12:00:00 AM
Firstpage
636
Lastpage
640
Abstract
A novel learning algorithm for a neuron-weighted associative memory (NWAM) is presented. The learning procedure is cast as a global minimization, solved by a gradient descent rule. An analog neural network for implementing the learning method is described. Some computer simulation experiments are reported
Keywords
content-addressable storage; learning (artificial intelligence); neural chips; neural nets; NWAM; analog neural network; associative memories; computer simulation experiments; global minimization; gradient descent rule; hardware implementation; learning algorithm; neuron-weighted associative memory; Associative memory; CADCAM; Computer aided manufacturing; Cost function; Hardware; Intelligent networks; Learning systems; Neural networks; Neurons; Stability;
fLanguage
English
Journal_Title
Computers, IEEE Transactions on
Publisher
ieee
ISSN
0018-9340
Type
jour
DOI
10.1109/12.223686
Filename
223686
Link To Document