HMC CS 152 Textbook Slides, Fall 2003
These slides are keyed to the textbook NND. They were created by the authors of the book. Each slide is a full page in pdf form.
Chapter 1: Introduction
Chapter 2: Neural Network Models
Chapter 3: Illustrative Example
Chapter 4: Perceptrons
Chapter 5: Vector Spaces
Chapter 6: Linear Transformations, Eigenvalues
Chapter 7: Supervised Hebbian Learning
Chapter 8: Performance Surfaces
Chapter 9: Performance Optimization
Chapter 10: Widrow-Hoff Learning
Chapter 11: Backpropagation
Chapter 12: Variations on Backpropagation
Chapter 13: Associative Learning
Chapter 14: Competitive Networks
Chapter 15: Grossberg Network
Chapter 16: Adaptive Resonance Theory
Chapter 17: Stability
Chapter 18: Hopfield Network