Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Books and Book parts
  4. Handbook of Neural Computation
 
book/monograph

Handbook of Neural Computation

Fiesler, Emile
•
Beale, R.
1996

Many scientists and engineers now use neural networks to tackle problems that are either intractable, or unrealistically time consuming to solve, through traditional computational strategies. To address the need for speedy dissemination of new ideas in this field to a broad spectrum of neural network users, designers and implementers, Oxford University Press and the Institute of Physics have joined forces to create a major reference publication devoted to neural network fundamentals, models, algorithms, applications and implementations. This work is intended to become the standard reference resource for the neural network community. The Handbook of Neural Computation will be produced in parallel in two updatable formats, looseleaf paper and CD-ROM, and will be kept up to date by means of supplements published on a regular basis. Details of new architectures, algorithms and applications may be submitted to the Handbook editors for peer review and possible inclusion in a future supplement to the Handbook. In this way we will create a moving compendium of the state of the art of neural computation. Key features of the Handbook of Neural Computation: * A hands-on guide to the design and implementation of neural networks * A comprehensive source of reference for all neural network users, designers and implementers * Provides an information pathway between scientists and engineers in different disciplines who apply neural networks to generically similar problems * Provides timely information in a rapidly changing field

  • Details
  • Metrics
Type
book/monograph
ISBN

0-7503-0312-3

0-7503-0413-8

Editors
Fiesler, Emile
•
Beale, R.
Date Issued

1996

Publisher

Institute of Physics and Oxford University Press

Publisher place

New York, New York

Series title/Series vol.

The Computational Intelligence Library

Subjects

feedback network

•

self-organizing feature map

•

learning

•

software implementation

•

perceptron

•

time series analysis

•

neural computation

•

case study

•

neuron

•

signal processing

•

modelling of cognitive phenomena

•

fundamentals

•

functional-link network

•

neural-evolutionary system

•

data compression

•

connectionism

•

radial basis function

•

control

•

unsupervised learning

•

connectionist network

•

multilayer perceptron

•

speech processing

•

neocognitron

•

Hopfield network

•

recurrent neural network

•

pattern classification

•

image processing

•

fuzzy-neural system

•

adalaine

•

neural network

•

application

•

neural computing

•

neural expert system

•

madalaine

•

feedforward network

•

artificial neural network

•

associative memory

•

LVQ

•

combinatorial optimization

•

hybrid system

•

prediction

•

adaptive resonance theory

•

hardware implementation

•

topology

•

network analysis

•

training

•

backpropagation

•

bidirectional associative memory

•

supervised learning

•

ontogenic neural network

Note

The electronic version is expected in early 1997.

Written at

EPFL

EPFL units
LIDIAP  
Available on Infoscience
March 10, 2006
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/227650
Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés