Artificial Neural Networks/Introduction

Introduction Artificial neural networks are one of the most popular and promising areas of artificial intelligence research. Artificial Neural Networks are abstract computational models, roughly based on the organizational structure of the human brain. There are a wide variety of network architectures and Deep learning learning methods that can be combined to produce neural networks with different computational abilities. What is This Book About? This book is going to serve as a general-purpose overview of artificial neural networks, including network construction, use, and applications. Who is This Book For? This book is going to be aimed at advanced undergraduates and graduate students in the areas of computer science, mathematics, engineering, and the sciences. What Are The Prerequisites? Readers of this book are going to require a solid mathematical background that includes, but may not be limited to: Linear Algebra Abstract Algebra Calculus Students may also find some benefit in the following engineering texts: Signals and Systems Engineering Analysis Students who wish to implement the lessons learned in this book should be familiar with at least one general-purpose programming language or have a background in: MATLAB Programming Programmable Logic