DocumentCode
3442371
Title
MAN: mass attraction network
Author
Erdem, Mahmut Hilmi ; Ozturk, Yusuf
Author_Institution
Dept. of Comput. Eng., Ege Univ., Izmir, Turkey
Volume
6
fYear
1994
fDate
30 May-2 Jun 1994
Firstpage
455
Abstract
In this study, a binary associative memory, inspired from Newton´s mass attraction theory is proposed and some related analysis is given. In the model, memory items are considered as masses in the interior or at the corners of a hypercube. In recall, “attraction forces” are computed and the memory item, whose “force” is the greatest, becomes the output pattern. Since the operation of the model is highly parallel, the network is extremely fast. Retrieving a memory item takes only two steps. The proposed model has been observed to be superior to Hamming net, Hopfield network and Harmony theory in various aspects
Keywords
content-addressable storage; learning (artificial intelligence); neural nets; parallel processing; MAN; attraction forces; binary associative memory; hypercube; mass attraction network; output pattern; parallel operation; Associative memory; Computational modeling; Computer simulation; Cost function; Equations; Gravity; Hamming distance; Information theory; Pattern analysis; Simulated annealing;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1994. ISCAS '94., 1994 IEEE International Symposium on
Conference_Location
London
Print_ISBN
0-7803-1915-X
Type
conf
DOI
10.1109/ISCAS.1994.409624
Filename
409624
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