Description
Written with the beginner in mind, this volume offers an exceptionally clear and thorough introduction to neural network at an elementary level. It provides the clear survey of basic neural network architectures and learning rules. In it, We emphasize mathematical analysis of networks, methods for training network, and application of neural network to practical engineering problems in speech recognition, stock market prediction and pattern recognition.
Table of Contents
Chapter 1: Fundamentals of Neural Networks
Chapter 2: Perceptrons
Chapter 3: Backpropagation
Chapter 4: Adaline and Madaline
Chapter 5: Supervised and Unsupervised Learning
Chapter 6: Counter-propagation Network
Chapter 7: Adaptive Resonance Theory
Chapter 8: Neocognitron
Chapter 9: Bidirectional Associative Memory
Chapter 10: Case Studies
Author
Ikvinderpal Singh
Ikvinderpal Singh, is Lecturer of P.G. Deptt. Of Computer Science & Applications, Khalsa College, Amritsar which is a premier institute in North India. He obtained his MCA with distinction from Guru Nanak Dev University, Amritsar. He has always been excellence right from his student carrer. He has written five books. He brought name for himself when he topped the college in B.Sc. His other areas of interest include Fuzzy systems, digital electronics and java programming.
Rachhpal Singh
Rachhpal Singh is head of P.G. Dept. Computer Science & Applications, Khalsa College, Amritsar which is a premier institute in North India. He obtained his MCA from thapar Institute of Engineering and Technology, patiala. He has over fifteen years of teaching experience to teach post graduate classes. He is an international author of the world level and his other areas of interest include software engineering, parallel processing system level programming.
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