MATLAB and Simulink Based Books
Written for courses in pattern recognition and neural networks, this book discusses the theory and practical application of neural networks. Topics covered include parameter optimization algorithms, density modeling, single layer networks, multi-layer perceptron, bayesian techniques, and gaussian processes. All examples are implemented with Netlab, a collection of neural network and pattern recognition M-files.
Companion Software: A set of MATLAB M-files is available.
Teaching materials based on MATLAB and Simulink