Artificial Neural Networks
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.
- Fundamentals of Neural Networks
- Perceptrons
- Backpropagation
- Adaline and Madaline
- Supervised and Unsupervised Learning
- Counter-propagation Network
- Adaptive Resonance Theory
- Neocognitron
- Bidirectional Associative Memory
- Case Studies
Ikvinderpal Singh
Dr. Ikvinderpal Singh is an Assistant Professor at Trai Shatabdi Guru Gobind Singh Khalsa college Amritsar, bringing 17+ years of academic leadership and research experience to the field of computer science. A Gold Medalist in B.Sc. IT, with an MCA (Distinction) and a Ph.D. in Neural Networks and Image Processing, he is known for blending rigorous research with practical innovation. A prolific academic creator, he has authored 37 books, published 82+ research papers, and designed 100+ industry-aligned skill-development courses. His expertise extends to doctoral evaluation, supervision, and active participation on 100+ editorial and review boards worldwide.
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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