Neural Networks: EURASIP Workshop 1990 Sesimbra, Portugal, February 15-17, 1990. Proceedings by Luis B. AlmeidaNeural Networks: EURASIP Workshop 1990 Sesimbra, Portugal, February 15-17, 1990. Proceedings by Luis B. Almeida

Neural Networks: EURASIP Workshop 1990 Sesimbra, Portugal, February 15-17, 1990. Proceedings

EditorLuis B. Almeida

Paperback | January 24, 1990

Pricing and Purchase Info

$64.95

Earn 325 plum® points

Prices and offers may vary in store

Quantity:

In stock online

Ships free on orders over $25

Not available in stores

about

The EURASIP workshop contributions collected in this volume have an interdisciplinary character. The authors include psychologists, biologists, engineers and mathematicians as well as computer scientists. The volume starts with two invited papers, by George Cybenko and by Eric Baum, on the formal study of the capabilities of neural networks. The following papers are organized into parts dealing with theory and algorithms, speech processing, image processing, and implementation. The workshop was sponsored by the European Association for Signal Processing without restriction on the origin of participants.
Title:Neural Networks: EURASIP Workshop 1990 Sesimbra, Portugal, February 15-17, 1990. ProceedingsFormat:PaperbackDimensions:286 pagesPublished:January 24, 1990Publisher:Springer Berlin HeidelbergLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3540522557

ISBN - 13:9783540522553

Look for similar items by category:

Reviews

Table of Contents

When are k-nearest neighbor and back propagation accurate for feasible sized sets of examples?.- Complexity theory of neural networks and classification problems.- Generalization performance of overtrained back-propagation networks.- Stability of the random neural network model.- Temporal pattern recognition using EBPS.- Markovian spatial properties of a random field describing a stochastic neural network: Sequential or parallel implementation?.- Chaos in neural networks.- The "moving targets" training algorithm.- Acceleration techniques for the backpropagation algorithm.- Rule-injection hints as a means of improving network performance and learning time.- Inversion in time.- Cellular neural networks: Dynamic properties and adaptive learning algorithm.- Improved simulated annealing, Boltzmann machine, and attributed graph matching.- Artificial dendritic learning.- A neural net model of human short-term memory development.- Large vocabulary speech recognition using neural-fuzzy and concept networks.- Speech feature extraction using neural networks.- Neural network based continuous speech recognition by combining self organizing feature maps and Hidden Markov Modeling.- Ultra-small implementation of a neural halftoning technique.- Application of self-organising networks to signal processing.- A study of neural network applications to signal processing.- Simulation machine and integrated implementation of neural networks.- VLSI implementation of an associative memory based on distributed storage of information.