Stanimirovic I. Applied Neural Networks and Soft Computing

Handbook. — Oakville, Arcler Press, 2019. — 212 p.
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.Differences Between The Brain and A Computer
Artificial Neural Networks
Definition and Characteristics
Processing Stages
Training or LearningApplication of an Intelligent Hopfield Neural Networks For Face Recognition
Methods And Techniques In Face Recognition Of Digital Images
Face Recognition Using Artificial Neural Networks
Feature Extraction Techniques
Pattern Recognition
Association and Classification
Natural Language Processing
Network Layer: Perceptron, Adaline, And Madaline
Backpropagation
ValidationArtificial Neural NetworksAnalogy With The Brain
Neural Networks
Network Operation
Operation of The Layers
What Makes The Different Neurocomputation?
Pattern Recognition
Power Synthesis
Frank Rosenblatt’s Perceptron
BackpropagationNeural Networks Applied to the Analysis of Images
Introduction To Patterns In Image Recognition
Digital Images
Applying Neural NetworksImage Analysis System
System Structure
Analysis of The Image
Architecture
Image Processing
Training ProcessDesign and Construction of A System For Detecting Electromyographic Signals Using Neural Networks
Electrodes
Electromyography
Electronic Fundamentals
The Electromyograph
Design And Construction Of The Prototype For The Acquisition of Electromyographic Signals With Bipolar Source