New developments in neural computing : proceedings of a meeting on neural computing sponsored by the Institute of Physics and the London Mathematical Society held in London, 19-21 April 1989
著者
書誌事項
New developments in neural computing : proceedings of a meeting on neural computing sponsored by the Institute of Physics and the London Mathematical Society held in London, 19-21 April 1989
A. Hilger, c1989
大学図書館所蔵 全29件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
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注記
Includes bibliographical references
内容説明・目次
内容説明
Research in neural computing is advancing rapidly at present, with important developments being made constantly. In such a fast-moving field it is important for workers to have access to the most up-to-date results, and this book, containing new information from researchers from all over the world, fulfills that need. New Developments in Neural Computing comprises the proceedings of a workshop on neural computing held in London in April 1989. The book begins with four tutorials, intended for beginners in the field, giving an introduction to some of the major topics in neural computing. There follow fifteen contributed papers on a wide variety of topics of current interest, and four invited papers by acknowledged world experts in particular areas. Eduardo Caianello (Italy), one of the founding fathers of the subject, writes on synthesising nets made up of binary decision elements, John Daugman (USA) discusses visual coding and Gabor functions, Rolfe Eckmiller (Germany) covers visuo-motor control in robots and Patrick Gallinari (France) discusses feedforward nets and their learning rules. New Developments in Neural Computing presents the state of the art in neural net research, and so is an important book for anyone interested in the mathematics and physics of the brain, computer science, neurophysiology and brain science in general. It will also be of interest to undergraduate students studying this new field.
目次
Tutorials: Feedforward networks - a tutorial (D Cohen and J Shawe-Taylor). Spin glasses and neural networks (D Sherrington). Living neural nets (J G Taylor). Implementing neural nets (L S Smith). Contributed papers: A self-organizing feedforward network applied to acoustic data (P D Hewitt, P J C Skitt and R C Witcomb). Realisation of self organising neural maps in 0,1 space (N M Allison and M J Johnson). A net incorporating feedback, for recognising poorly drawn characters (R N Banks and D G Elliman). Vector coding and multiplicative gain control in the nervous system of the crab (P J Fraser). User modelling by classification: a neural-based approach (R Beale, J Finlay, J Austin and M Harrison). A new model of the neuron (D Gorse). The achievement of memory by an antiphon structure (P Whittle). Hard learning in Boolean neural networks (J L Shapiro). The maximum storage capacity in Boolean associative memories (K Y M Wong and D Sherrington). Matched filter model for design of neural networks (D R Selviah and J E Midwinter). Neural network models with sign constrained weights (C Campbell). Neural networks and random iterative maps (P C Bressloff). A neurocomputer exploiting silicon compilation (M M B R Vellasco and P C Treleaven). NIL-PLUS: a neural network implementation language (A S Bavan). PYGMALION: a European neural computing research project (M K O Lee). Invited Papers: A study of neuronic equations (E R Caianiello). Some properties of linear multilayer perceptrons (P Gallinari). Neural control of intelligent robots (R Eckmiller). Non-orthogonal wavelet representations in relaxation networks: image encoding and analysis with biological visual primitives (J Daugman).
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