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Publication detail
DAO ANH, M.
Original Title
Optimal Linear Neural Associative Memory Using for Pattern Association
Type
article in a collection out of WoS and Scopus
Language
English
Original Abstract
The paper delas with an optimal linear associative (OLAM) neural network. The network consists of two layers: input layer X and output layer Y. There is a full set of connections between input and output layers. The OLAM principle and it structure, learning an recalling algorithms and some experiments with OLAM are described in the paper.
Keywords
associative memory, neural network, optimal linear associative memory
Authors
Released
1. 1. 2000
Location
Ostrava
ISBN
80-85988-44-5
Book
34th Spring International Conference Modelling and Simulation of Systems MOSIS 2000
Pages from
71
Pages to
74
Pages count
4
BibTex
@inproceedings{BUT5753, author="Minh {Dao Anh}", title="Optimal Linear Neural Associative Memory Using for Pattern Association", booktitle="34th Spring International Conference Modelling and Simulation of Systems MOSIS 2000", year="2000", pages="71--74", address="Ostrava", isbn="80-85988-44-5" }