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パターンモデルを用いた不動点探索形連想記憶システム方程式
https://bunkyo.repo.nii.ac.jp/records/3444
https://bunkyo.repo.nii.ac.jp/records/3444cd18d1be-f613-46a7-a8c8-94c13019d585
名前 / ファイル | ライセンス | アクション |
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BKSJ150009.pdf (1.3 MB)
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Item type | 紀要論文 / Departmental Bulletin Paper(1) | |||||
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公開日 | 2012-01-17 | |||||
タイトル | ||||||
タイトル | パターンモデルを用いた不動点探索形連想記憶システム方程式 | |||||
タイトル | ||||||
タイトル | An Associative Memory System Equation of Fixed-Point Searching Type Using a Pattern-Model | |||||
言語 | ||||||
言語 | jpn | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | departmental bulletin paper | |||||
著者 |
鈴木, 昇一
× 鈴木, 昇一× 佐久間, 拓也 |
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著者 | ||||||
Suzuki, Shoichi | ||||||
著者 | ||||||
Sakuma, Takuya | ||||||
所属機関 | ||||||
文教大学情報学部 | ||||||
所属機関 | ||||||
文教大学情報学部 | ||||||
所属機関 | ||||||
Bunkyo University Faculty of Information and Communications | ||||||
所属機関 | ||||||
Bunkyo University Faculty of Information and Communications | ||||||
内容記述 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | It is presented here that an associative neural-network binary memory system on n-dimensional Euclidean space Rn suggested by K. Nijima is able to be extended to a system on any separable Hilbert space ◆◆ using a corresponding pattern model Tφ of a pattern φ proposed by S. Suzuki. Applying to a problem concerning at how many stages a pattern-recognition process converges practically an iterative scheme suggested by P. Alfeld which can give a solution of a fixed-point equation on Rn, it is shown that the process has a solution of a constrained minimization problem. By virtue of this research, the associative system may act upon unitary-transformation invariances such as rotations, scalings, and translations, etc. or perceptual constancies appearing in the psychology, and a design of its weights and thresholds and a evaluation about a convergence of the associatively recalling process may be precisely shown. \n 可分なHilbert空間◆◆の元としてのパターンφの,S.Suzukiの提案したパターンモデルTφを用いれば,ユークリッド空間.Rnでの新島耕一による"連想記憶のニューラルネット2値モデル"が◆◆へと拡張され,然も,RnからRnへの写像に関するPeter Alfeldの "不動点方程式の解法としてのan iterative scheme" を適用して,本連想記憶モデルによるパターン認識過程が何段階でほぼ収束するかなどに関し, the constrained minimization problemの解として得られることが示されている。 本研究によって,可分なHilbert空間◆◆での連想形記憶ニューラルネットの2値モデルにユニタリ座標変換不変性(rotation, scaling, translation等に対する不変性,あるいは心理学でいう一種の知覚の恒常性)を備えさせることが可能になり,その重み・閾値の設計法,連想過程の収束の評価が精密にできるようになった。 |
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書誌情報 |
情報研究 en : Information and Communication Studies 巻 15, p. 97-128, 発行日 1994-01-01 |
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ISSN | ||||||
収録物識別子 | 03893367 | |||||
著者版フラグ | ||||||
出版タイプ | VoR | |||||
フォーマット | ||||||
内容記述タイプ | Other | |||||
内容記述 | application/pdf | |||||
本文言語 | ||||||
日本語 | ||||||
ID | ||||||
BKSJ150009 | ||||||
作成日 | ||||||
日付 | 2012-01-17 |