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Neural Networks: From Biology To High Energy Physics - Proceedings Of The Third Workshop

Author : Daniel J Amit
Publisher : World Scientific
Page : 310 pages
File Size : 28,96 MB
Release : 1995-10-18
Category :
ISBN : 9814548405

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The papers appearing in this proceedings volume cover a broad range of subjects, owing to the highly cross-disciplinary character of the workshop, and include: experiments and models concerning the dynamics of the neural activity in the cortex (DMS experiments, attractor dynamics in the cortex, spontaneous activity…); hippocampus, space and memory; theoretical advances in neural network modeling; information processing in neural networks; applications of neural networks to experimental physics, particularly to high energy physics; digital and analog hardware implementations of neural networks; etc.

Neural Networks

Author : Daniel J. Amit
Publisher : World Scientific Publishing Company Incorporated
Page : 294 pages
File Size : 10,61 MB
Release : 1995
Category : Science
ISBN : 9789810224820

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Neural Networks: From Biology To High Energy Physics - Proceedings Of The 2nd Workshop

Author : Omar Benhar
Publisher : World Scientific
Page : 358 pages
File Size : 14,65 MB
Release : 1993-10-16
Category :
ISBN : 9814553581

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Neural network models, in addition to being of intrinsic theoretical interest, have also proved to be a useful framework in which issues in theoretical biology can be put into perspective. These issues include, amongst others, modelling the activity of the cortex and the study of protein folding. More recently, neural network models have been extensively investigated as tools for data analysis in high energy physics experiments. These workshop proceedings reflect the strongly interdisciplinary character of the field and provide an updated overview of recent developments.

Handbook of Neural Computation

Author : E Fiesler
Publisher : CRC Press
Page : 1094 pages
File Size : 23,96 MB
Release : 2020-01-15
Category : Computers
ISBN : 1420050648

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The Handbook of Neural Computation is a practical, hands-on guide to the design and implementation of neural networks used by scientists and engineers to tackle difficult and/or time-consuming problems. The handbook bridges an information pathway between scientists and engineers in different disciplines who apply neural networks to similar probl