Introduction to Neural Networks Using MATLAB 6.0 by S.N. Sivanandam, S. Sumathi, and S.N. Deepa is a foundational academic text designed for undergraduate students in computer science and engineering. The book is widely recognized for integrating
Competitive and Boltzmann Learning: Advanced rules for self-organizing and stochastic models. Practical Implementation with MATLAB
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If you’re looking for a clear, hands-on introduction to artificial neural networks (ANNs) with MATLAB implementations, “Introduction to Neural Networks Using MATLAB” by S. N. Sivanandam (and co-authors S. Sumathi & S. N. Deepa) is a solid choice. Introduction to Neural Networks Using MATLAB 6
Fundamentals of ANNs: It explores the transition from biological neural networks (the human brain) to artificial models, detailing basic building blocks like network architecture, weights, biases, and activation functions.
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Full Title: Introduction to Neural Networks Using MATLAB 6.0 (often referred to with version 6.0 or later editions).
Author: S. Sivanandam (typically alongside S. N. Deepa).
Publisher: Tata McGraw-Hill Education.
Target Audience: Undergraduate/Postgraduate engineering students (CS, ECE, EE), researchers, and practitioners.
Download (Google Drive / Dropbox): [link] Sivanandam (typically alongside S. N. Deepa).
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