Neural Network Fundamentals with Graphs, Algorithms and Applications
Published on 1. January 1996
Book
Hardback
478 pages
978-0-07-006618-2 (ISBN)
Description
Aimed at senior undergraduate or first-year graduate courses in neural networks and neurocomputing, this work presents neural network theory for diverse applications in a unified way, where the structures of artificial neural networks are characterized by distinguished classes of graphs.
More details
Language
English
Place of publication
New York
United States
Publishing group
McGraw-Hill Education - Europe
Target group
College/higher education
Illustrations
bibliography
Dimensions
Height: 230 mm
Width: 165 mm
Weight
818 gr
ISBN-13
978-0-07-006618-2 (9780070066182)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Content
Part 1 Fundamentals: basics of neuroscience and artificial neuron models; graphs; algorithms. Part 2 Feedforward networks: perceptrons and LMS algorithm; complexity of learning using feedforward networks; adaptive structure networks. Part 3 Recurrent networks: symmetric and asymmetric recurrent network; competitive learning and self-organizing networks. Part 4 Applications of neural networks: neural networks approach to solving hard problems.