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タイトルSparse distributed memory and related models
本文(外部サイト)http://hdl.handle.net/2060/19920021480
著者(英)Kanerva, Pentti
著者所属(英)Research Inst. for Advanced Computer Science
発行日1992-04-01
言語eng
内容記述Described here is sparse distributed memory (SDM) as a neural-net associative memory. It is characterized by two weight matrices and by a large internal dimension - the number of hidden units is much larger than the number of input or output units. The first matrix, A, is fixed and possibly random, and the second matrix, C, is modifiable. The SDM is compared and contrasted to (1) computer memory, (2) correlation-matrix memory, (3) feet-forward artificial neural network, (4) cortex of the cerebellum, (5) Marr and Albus models of the cerebellum, and (6) Albus' cerebellar model arithmetic computer (CMAC). Several variations of the basic SDM design are discussed: the selected-coordinate and hyperplane designs of Jaeckel, the pseudorandom associative neural memory of Hassoun, and SDM with real-valued input variables by Prager and Fallside. SDM research conducted mainly at the Research Institute for Advanced Computer Science (RIACS) in 1986-1991 is highlighted.
NASA分類COMPUTER OPERATIONS AND HARDWARE
レポートNO92N30724
NASA-CR-190553
RIACS-TR-92.10
NAS 1.26:190553
権利No Copyright
URIhttps://repository.exst.jaxa.jp/dspace/handle/a-is/126402


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