NEURAL NETWORK FUNDAMENTALS WITH GRAPHS ALGORITHM

9780074635292: NEURAL NETWORK FUNDAMENTALS WITH GRAPHS ALGORITHM

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Bose
Published by McGraw Hill Education Pvt. Ltd.
ISBN 10: 0074635298 ISBN 13: 9780074635292
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Book Description McGraw Hill Education Pvt. Ltd. N.A. Book Condition: New. International Edition. Bookseller Inventory # 323424

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BOSE
Published by MCGRAW-HILL EDUCATION (INDIA) LTD
ISBN 10: 0074635298 ISBN 13: 9780074635292
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Book Description MCGRAW-HILL EDUCATION (INDIA) LTD. Book Condition: New. 0074635298 This is an International Edition. Brand New, Paperback, Delivery within 6-14 business days, Similar Contents as U.S Edition, ISBN and Cover design may differ, printed in Black & White. Choose Expedited shipping for delivery within 3-8 business days. We do not ship to PO Box, APO , FPO Address. In some instances, subjects such as Management, Accounting, Finance may have different end chapter case studies and exercises. International Edition Textbooks may bear a label "Not for sale in the U.S. or Canada" and "Content may different from U.S. Edition" - printed only to discourage U.S. students from obtaining an affordable copy. The U.S. Supreme Court has asserted your right to purchase international editions, and ruled on this issue. Access code/CD is not provided with these editions , unless specified. We may ship the books from multiple warehouses across the globe, including India depending upon the availability of inventory storage. Customer satisfaction guaranteed. Bookseller Inventory # RI9780074635292

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ISBN 10: 0074635298 ISBN 13: 9780074635292
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Book Description Paperback. Book Condition: New. This is an International Edition Brand New Paperback Same Title Author and Edition as listed. ISBN and Cover design differs. Similar Contents as U.S Edition. Standard Delivery within 6-14 business days ACROSS THE GLOBE. We can ship to PO Box address in US. International Edition Textbooks may bear a label "Not for sale in the U.S. or Canada" or "For sale in Asia only" or similar restrictions- printed only to discourage students from obtaining an affordable copy. US Court has asserted your right to buy and use International edition. Access code/CD may not provided with these editions. We may ship the books from multiple warehouses across the globe including Asia depending upon the availability of inventory. Printed in English. Customer satisfaction guaranteed. Bookseller Inventory # IS9780074635292

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N.K. Bose,Ping Liang
Published by McGraw Hill Education (1998)
ISBN 10: 0074635298 ISBN 13: 9780074635292
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Book Description McGraw Hill Education, 1998. Softcover. Book Condition: New. First edition. This text presents neural network theory for diverse applications in a unified way, where the structure of artificial neural networks are characterized by distinguished classes of graphs. The book first provides a clear but concise exposition of neuroscience fundamentals, graph theory and alogorithms. It then moves to a detailed analysis of perceptron and lms-theory based neural networks, multilayer feedforward networks, and self-organizing competitive learning neural networks. The text culminates with a chapter on selected applications. Table of contents PART I: FUNDAMENTALS Chapter 1 Basics of Neuroscience and Artificial Neuron Models Chapter 2 Graphs Chapter 3 Algorithms PART II: FEEDFORWARD NETWORKS Chapter 4 Perceptions and LMS Algorithm Chapter 5 Multilayer Networks Chapter 6 Complexity of Learning Using Feedforward Networks Chapter 7 Adaptive Structure Networks PART III: RECURRENT NETWORKS Chapter 8 Symmetric and Asymmetric Recurrent Networks Chapter 9 Competitive Learning and Self-Organizing Networks PART IV: APPLICATIONS OF NEURAL NETWORKS Chapter 10 Neural Networks Approach to Solving Hard Problems Appendix A: Basis of Gradient-Based Optimization Methods Index Printed Pages: 484. Bookseller Inventory # 17450

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N.K. Bose,Ping Liang
Published by McGraw Hill Education (1998)
ISBN 10: 0074635298 ISBN 13: 9780074635292
New Softcover First Edition Quantity Available: > 20
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A - Z Books
(New Delhi, DELHI, India)
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Book Description McGraw Hill Education, 1998. Softcover. Book Condition: New. First edition. This text presents neural network theory for diverse applications in a unified way, where the structure of artificial neural networks are characterized by distinguished classes of graphs. The book first provides a clear but concise exposition of neuroscience fundamentals, graph theory and alogorithms. It then moves to a detailed analysis of perceptron and lms-theory based neural networks, multilayer feedforward networks, and self-organizing competitive learning neural networks. The text culminates with a chapter on selected applications. Table of contents PART I: FUNDAMENTALS Chapter 1 Basics of Neuroscience and Artificial Neuron Models Chapter 2 Graphs Chapter 3 Algorithms PART II: FEEDFORWARD NETWORKS Chapter 4 Perceptions and LMS Algorithm Chapter 5 Multilayer Networks Chapter 6 Complexity of Learning Using Feedforward Networks Chapter 7 Adaptive Structure Networks PART III: RECURRENT NETWORKS Chapter 8 Symmetric and Asymmetric Recurrent Networks Chapter 9 Competitive Learning and Self-Organizing Networks PART IV: APPLICATIONS OF NEURAL NETWORKS Chapter 10 Neural Networks Approach to Solving Hard Problems Appendix A: Basis of Gradient-Based Optimization Methods Index Printed Pages: 484. Bookseller Inventory # 17450

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