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ID 15443
Eprint ID
15443
フルテキストURL
著者
奈良 重俊 Department of Electrical and Electronic Engineering
Banzhaf Wolfgag Central Research Laboratory, Mitsubishi Electric Corporation
抄録
An information processing task which generates combinatorial explosion and program complexity when it is treated by a serial algorithm is investigated using both Genetic Algorithms (GA) and a neural network model (NN). The task in question is to find a target memory from a set of stored entries in the form of "attractors" in a high dimensional state space. The representation of entries in the memory is distributed ("an auto associative neural network" in this paper), and the problem is to find an attractor under a given access information where the uniqueness or even existence of a solution is not always guaranteed ( an ill-posed problem ). The GA is used as an algorithm for generating a search orbit to search effectively for a state which satisfies the access condition and belongs to the target attractor basin in state space. The NN is used to retrieve the corresponding entry from the network. The results of our computer simulation indicate that the present method is superior to a search method which uses random walk in state space. Our technique may prove useful in the realization of flexible and adaptive information processing, since pattern search in high dimensional state spaces is common in various kinds of parallel information processing.
発行日
1992-03-28
出版物タイトル
Memoirs of the Faculty of Engineering, Okayama University
出版物タイトル(別表記)
岡山大学工学部紀要
26巻
2号
出版者
Faculty of Engineering, Okayama University
出版者(別表記)
岡山大学工学部
開始ページ
111
終了ページ
128
ISSN
0475-0071
NCID
AA10699856
資料タイプ
紀要論文
言語
English
OAI-PMH Set
岡山大学
論文のバージョン
publisher
査読
無し
Sort Key
9
Eprints Journal Name
mfe