Cantitate/Preț
Produs

Neural Network Perspectives on Cognition and Adaptive Robotics

Editat de A Browne
en Limba Engleză Hardback – 1997
Featuring an international team of authors, Neural Network Perspectives on Cognition and Adaptive Robotics presents several approaches to the modeling of human cognition and language using neural computing techniques. It also describes how adaptive robotic systems can be produced using neural network architectures. Covering a wide range of mainstream area and trends, each chapter provides the latest information from a different perspective.
Citește tot Restrânge

Preț: 86483 lei

Preț vechi: 141117 lei
-39% Nou

Puncte Express: 1297

Preț estimativ în valută:
15301 17826$ 13362£

Comandă specială

Livrare economică 29 decembrie 25 - 12 ianuarie 26

Doresc să fiu notificat când acest titlu va fi disponibil:

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9780750304559
ISBN-10: 0750304553
Pagini: 270
Dimensiuni: 187 x 235 x 22 mm
Greutate: 0.59 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press

Public țintă

Professional

Cuprins

Part 1 Representation: Challenges for neural computing. Representing structure and structured representations in connectionist networks. Chaos, dynamics and computational power in biologically plausible neural networks. Information-theoretic approaches to neural network learning. Part 2 Cognitive modelling: Exploring different approaches towards everyday commonsense reasoning. Natural language processing with subsymbolic neural networks. The relational mind. Neuroconsciousness: a fundamental postulate. Part 3 Adaptive robotics: The neural mind and the robot. Teaching a robot to see how it moves. Designing a nervous system for an adaptive mobile robot.

Descriere

Featuring an international team of authors, Neural Network Perspectives on Cognition and Adaptive Robotics presents several approaches to the modeling of human cognition and language using neural computing techniques. It also describes how adaptive robotic systems can be produced using neural network architectures. Covering a wide range of mainstream area and trends, each chapter provides the latest information from a different perspective.