New Developments in Neural Computing (inbunden)
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Format
Inbunden (Hardback)
Språk
Engelska
Antal sidor
264
Utgivningsdatum
1989-01-01
Förlag
Institute of Physics Publishing
Illustrationer
104 line drawings, 11 half-tones
Komponenter
vi, 253 p. :
ISBN
9780852741931

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, 19th-21st April 1989

av John Taylor, C L T Mannion
Inbunden,  Engelska, 1989-01-01
1099
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This volume consists of the proceedings of a conference on neural computing, held at King's College, London in April 1989 and sponsored by the British Institute of Physics and the London Mathematical Society. The papers present both introductory lectures, contributed research papers, and invited contributions from world experts, in order to provide a representative picture of the state of neural network research both in the UK and the rest of the world. The meeting brought to light distinct differences of view between the spin glass (statistical mechanics) community and the more biologically-oriented modellers. This was particularly clear with respect to the importance of the inclusion of detailed membrane and timing effects in neurons and between them. Topics covered included multi-layer perceptrons and their learning rules, the statistical-mechanical approach to neural networks, simulation languages and hardware, and the neuro-biological properties of living neural nets.
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John Taylor, C L T Mannion

Innehållsförteckning

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; a self-organizing feedforward network applied to acoustic data, P.D.Hewitt, et al; realization of self-organizing neural maps inspace, N.M.Alinson 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 constrainted 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.

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