شبکه‌های عصبی کاربردی و محاسبات نرم

Cover Half Title Page Title page Copyright Page About the Author Table of Contents List of Figures List of Tables Preface Chapter 1 Introduction 1.1. Differences Between The Brain and A Computer 1.2. Artificial Neural Networks 1.3. Definition and Characteristics 1.4. Processing Stages 1.5. Training or Learning Chapter 2 Application of an Intelligent Hopfield Neural Networks For Face Recognition 2.1. Methods And Techniques In Face Recognition Of Digital Images 2.2. Face Recognition Using Artificial Neural Networks 2.3. Feature Extraction Techniques 2.4. Pattern Recognition 2.5. Association and Classification2.6. Natural Language Processing 2.7. Network Layer: Perceptron, Adaline, And Madaline 2.8. Backpropagation 2.9. Validation Chapter 3 Artificial Neural Networks 3.1. Introduction 3.2. Analogy With The Brain 3.3. Neural Networks 3.4. Network Operation 3.5. Operation of The Layers 3.6. What Makes The Different Neurocomputation 3.7. Pattern Recognition 3.8. Power Synthesis 3.9. Frank Rosenblatt's Perceptron 3.10. Backpropagation Chapter 4 Neural Networks Applied to the Analysis of Images 4.1. Introduction To Patterns In Image Recognition 4.2. Digital Images4.3. Applying Neural Networks Chapter 5 Image Analysis System 5.1. System Structure 5.2. Analysis of The Image 5.3. Architecture 5.4. Image Processing 5.5. Training Process Chapter 6 Design and Construction of A System For Detecting Electromyographic Signals Using Neural Networks 6.1. Electrodes 6.2. Electromyography 6.3. Electronic Fundamentals 6.4. The Electromyograph 6.5. Design And Construction Of The Prototype For The Acquisition of Electromyographic Signals With Bipolar Source Chapter 7 Conclusions Bibliography Index

Applied Neural Networks and Soft Computing examines the relation between neural networksand soft computing. Neural network is a system of hardware and software designedafter the operations of neurons. Applied neural networks has a plethora of applicationsand the text tries to touch every aspect to give readers a wider perspective. Further, artificialneural networks (vaguely inspired by biological neural network) are also discussed tokeep readers up to date regarding the latest innovations taking place.

Applied Neural Networks and Soft Computing examines the relation between neural networks and soft computing. Neural network is a system of hardware and software designed after the operations of neurons. Applied neural networks has a plethora of applications and the text tries to touch every aspect to give readers a wider perspective. Further, artificial neural networks (vaguely inspired by biological neural network) are also discussed to keep readers up to date regarding the latest innovations taking place. Examines various aspects of simulations, including an extensive overview of computational and numerical simulations. The book includes an introduction to system dynamics simulations, implementation of system dynamics for urban planning in a municipality, and dynamic integrated framework for improving software processes.