Neural Networks: EURASIP Workshop 1990 Sesimbra, Portugal, February 15-17, 1990. Proceedings: Lecture Notes in Computer Science, cartea 412
Editat de Luis B. Almeida, Christian J. Wellekensen Limba Engleză Paperback – 24 ian 1990
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Specificații
ISBN-13: 9783540522553
ISBN-10: 3540522557
Pagini: 292
Ilustrații: XIII, 279 p.
Dimensiuni: 216 x 279 x 15 mm
Greutate: 0.42 kg
Ediția:1990
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Lecture Notes in Computer Science
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3540522557
Pagini: 292
Ilustrații: XIII, 279 p.
Dimensiuni: 216 x 279 x 15 mm
Greutate: 0.42 kg
Ediția:1990
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Lecture Notes in Computer Science
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
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.