DocumentCode
1625304
Title
Discrete dynamic neural memories: training and performance
Author
Hassoun, Mohamad H.
Author_Institution
Dept. of Electr. & Comput. Eng., Wayne State Univ., Detroit, MI, USA
fYear
1989
Firstpage
470
Abstract
A discrete dynamic associative neural memory (DAM) has a regular layered structure of simple neural processing units with feedback that is ideal for optimal implementations. DAM is reviewed for both autoassociative and heteroassociative processing. Several optimal DAM recording/learning algorithms and learning strategies are reviewed. Important DAM dynamics and performance characteristics are discussed and compared for various DAM synthesis techniques
Keywords
content-addressable storage; learning systems; memory architecture; neural nets; DAM; autoassociative processing; discrete dynamic associative neural memory; feedback; heteroassociative processing; learning strategies; neural processing units; recording/learning algorithms; regular layered structure; synthesis techniques; Associative memory; Capacity planning; Convergence; Neurons; Nonlinear optical devices; Nonlinear optics; Optical arrays; Optical interconnections; Optical recording; Pain;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1989., IEEE International Symposium on
Conference_Location
Portland, OR
Type
conf
DOI
10.1109/ISCAS.1989.100392
Filename
100392
Link To Document