Neuroscience: From Neural Networks to Artificial Intelligence: Proceedings of a U.S.-Mexico Seminar held in the city of Xalapa in the state of 1991

Rudomin, Pablo & Michael A. Arbib & Francisco Cervantes-Perez & Ranulfo Romo (eds)

ISBN 10: 3540565019 / ISBN 13: 9783540565017

Verlag: Springer, 1993

Beschreibung

Wraps and page edges shelf worn and thumbed. Rear of wraps show some small creases. Photos upon request. International shipping billed at cost.; Text body is clean and unmarked. Large/heavy book: international buyers may be charged for additional shipping costs.; Research Notes in Neural Computing 4; 8vo 8" - 9" tall; 579 pages. Bestandsnummer des Verkäufers 74188

Bibliografische Details

Titel: Neuroscience: From Neural Networks to ...

Verlag: Springer

Erscheinungsdatum: 1993

Einband: Softcover

Zustand: Very Good-

Zustand des Schutzumschlags: No Dust Jacket As Issued

Über diesen Titel

Inhaltsangabe:

The Central Nervous System can be considered as an aggregate of neurons specialized in both the transmission and transformation of information.Information here has been used for many purposes, but the most important oneis probably to generate a representation of the "external" world that allows the organism to react properly to changes in its external environment. These functions range from such basic ones as detection of changes that may lead to tissue damage and eventual destruction of the organism and the implementation of avoidance reactions to more elaborate representations of the external world implying recognition of shapes, sounds and textures as the basis of planned action or even reflection. The question is, how can we hope to understand the complexity inherent in this range of functionalities? One of the distinguishing features of the last two decades has been the availability of computational power that has impacted the many areas of science concerned with this question. An effort has been made within this book to cross boundaries and to have active scientists from different backgrounds and disciplines explain the basic principles which guide their investigations with the hope that this will lay the basis for a future collaborative effort to understand the principles of neural networks.

Reseña del editor:

The Central Nervous System can be considered as an aggregate of neurons specialized in both the transmission and transformation of information. Information can be used for many purposes, but probably the most important one is to generate a representation of the "external" world that allows the organism to react properly to changes in its external environment. These functions range from such basic ones as detection of changes that may lead to tissue damage and eventual destruction of the organism and the implementation of avoidance reactions, to more elaborate representations of the external world implying recognition of shapes, sounds and textures as the basis of planned action or even reflection. Some of these functions confer a clear survival advantage to the organism (prey or mate recognition, escape reactions, etc. ). Others can be considered as an essential part of cognitive processes that contribute, to varying degrees, to the development of individuality and self-consciousness. How can we hope to understand the complexity inherent in this range of functionalities? One of the distinguishing features of the last two decades has been the availability of computational power that has impacted many areas of science. In neurophysiology, computation is used for experiment control, data analysis and for the construction of models that simulate particular systems. Analysis of the behavior of neuronal networks has transcended the limits of neuroscience and is now a discipline in itself, with potential applications both in the neural sciences and in computing sciences.