Nerual Network Design(神经网络设计, Hagan)

Nerual Network Design (2nd Edition) Content Ch 2 Neuron Model and Network Architectures Ch 3 An Illustrative Example Ch 4 Perceptron Learning Rule Ch 5 Signal and Weight Vector Spaces Ch 6 Linear Transformations for Neural Networks Ch 7 Supervised Hebbian Learning Ch 8 Performance Surfaces and Optimum Points Ch 9 Performance Optimization Ch 10 Widrow-Hoff Learning Ch 11 Backpropagation Ch 12 Variations on Backpropagation Ch 13 Generalization Ch 14 Dynamic Networks Ch 15 Associative Learning Ch 16 Competitive Networks Ch 17 Radial Basis Networks Ch 18 Grossberg Network Ch 19 Adaptive Resonance Theory Ch 20 Stability Ch 21 Hopfield Network Ch 22 Practical Training Issues Ch 23 Case Study 1:Function Approximation Ch 24 Case Study 2:Probability Estimation Ch 25 Case Study 3:Pattern Recognition Ch 26 Case Study 4: Clustering Ch 27 Case Study 5: Prediction