Synopsis
This textbook brings together an identifiable core of ideas, techniques and applications which characterize the emerging field of artificial neural networks. Features include: numerous exercises which could also be expanded into projects and thesis work; each new topic is preceded with a reduced complexity example of the concept; key concepts and related mathematical analysis are developed in a concise and logical way; and there is discussion of genetic algorithms.This book is a must read. Artificial Neural Networks brings together an identifiable core of ideas, techniques, and applications that characterize this emerging field. The text is intended for beginning graduate/advanced undergraduate students as well as practicing engineers and scientists. The text is suitable for use in a one- or two-semester course and may be supplemented by individual student projects and readings from the literature. Numerous exercises are presented to challenge and motivate the reader to further explore relevant concepts. Many of these exercises can be expanded into projects and thesis work. No previous experience in this field is assumed, although readers familiar with signal processing, linear algebra, pattern recognition, and other related areas will find the book easier to read. The book is meant to be largely self-contained and suitable for students in the disciplines of electrical and computer engineering, computer science, mathematics, physics, and related disciplines.
About the Author
Mathematics Class-10 is written by RD Sharma.
