Applied Neural Networks and Soft Computing
Published on 30. January 2019
234 pages
978-1-77361-586-8 (ISBN)
Description
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.
More details
Content
- 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 Classification
- 2.6. 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 Images
- 4.3. 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
