Artificial neural networks : concept learning / edited by Joachim Diederich.

Contributor(s): Diederich, JoachimSeries: IEEE Computer Society neural networks technology seriesPublisher: Los Alamitos, Calif. : IEEE Computer Society Press, c1990Description: vii, 141 p. : ill. ; 28 cmISBN: 0818620153 (pbk.); 0818660155 (microfiche); 0818690151 (case)Subject(s): Artificial intelligence | Neural computers | Neural networks (Computer science)DDC classification: 006.3,ART
Contents:
Artificial Neural Network Concept, Learning An Introduction (Page-1), Connectionist Learning Procedures (Page-11), Dynamic Connections in Neural Networks (Page-48), Connectionist Recruitment Learning (Page-63), The ART of Adaptive Pattern Recognition by a Self Organizing Neural Networks (Page-69), Neuronlike Adaptive Elements That Can Solve Difficult Learning Control Problems (Page-81), On The Use of Background in Associative Reinforecement Learning (Page-94), A Learning Rule for Asynchronous Perceptrons with Feedback in a Combinatorial Environment (Page-102), Deterministic Boltzmann Learning Performs Steepest in Weight Space (Page-128).
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Item type Current location Home library Shelving location Call number URL Status Notes Date due Barcode Item holds
Book Book Military College of Signals (MCS)
Military College of Signals (MCS)
General Stacks 006.3,ART (Browse shelf) Link to resource Available Almirah No. 109, Shelf No. 3 MCS368
Book Book Military College of Signals (MCS)
Military College of Signals (MCS)
General Stacks 006.3,ART (Browse shelf) Link to resource Available Almirah No.7, Shelf No.1 MCS369
Book Book Military College of Signals (MCS)
Military College of Signals (MCS)
General Stacks 006.3,ART (Browse shelf) Link to resource Available Almirah No. 109, Shelf No. 3 MCS370
Total holds: 0

Artificial Neural Network Concept, Learning An Introduction (Page-1), Connectionist Learning Procedures (Page-11), Dynamic Connections in Neural Networks (Page-48), Connectionist Recruitment Learning (Page-63), The ART of Adaptive Pattern Recognition by a Self Organizing Neural Networks (Page-69), Neuronlike Adaptive Elements That Can Solve Difficult Learning Control Problems (Page-81), On The Use of Background in Associative Reinforecement Learning (Page-94), A Learning Rule for Asynchronous Perceptrons with Feedback in a Combinatorial Environment (Page-102), Deterministic Boltzmann Learning Performs Steepest in Weight Space (Page-128).

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