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Artificial Neural Network Training and Software Implementation Techniques
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Authors: Ali Kattan, Rosni Abdullah and Zong Woo Geem (Universiti Sains Malaysia, Penang, Malaysia) 
Book Description:
Artificial neural networks (ANN) are widely used in diverse fields of science and industry. Though there have been numerous techniques used for their implementations, the choice of a specific implementation is subjected to different factors including cost, accuracy, processing speed and overall performance. Featured with synaptic plasticity, the process of training is concerned with adjusting the individual weights between each of the individual ANN neurons until we can achieve close to the desired output. This book introduces the common trajectory-driven and evolutionary-based ANN training algorithms. (Imprint: Novinka Books)

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Table of Contents:
Preface pp.i-vii

1. INTRODUCTION, pp. 1-2

2. FEED-FORWARD NEURAL NETWORKS, pp. 3-10

3. FFANN SOFTWARE SIMULATION, pp. 11-16

4. FFANN TRAINING CONCEPT, pp. 17-22

5. TRAJECTORY-DRIVEN TRAINING PARADIGM, pp. 23-26

6. EVOLUTIONARY-BASED TRAINING PARADIGM, pp. 27-36

7. FFANN SIMULATION UTILIZING GRAPHIC-PROCESSING UNITS, pp. 37-40

8. CONCLUSION, pp. 41-42

INDEX pp.55-58

   Series:
      Computer Networks
   Binding: Softcover
   Pub. Date: 2011
   Pages: 65 pp., 5.5 x 8.5 (NBC - C)
   ISBN: 978-1-61122-990-5
   Status: AV
  
Status Code Description
AN Announcing
FM Formatting
PP Page Proofs
FP Final Production
EP Editorial Production
PR At Prepress
AP At Press
AV Available
  
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Artificial Neural Network Training and Software Implementation Techniques