ECE/CS/ME 539 Lecture Notes (power point files)

Last Modified: Monday, September 13, 2004

• Lecture 1 Overview of the course (PDF)
• Lecture 2 Applications of Artificial Neural Network (PDF)
• Lecture 3 Basic Definitions of ANN (PDF)
• Lecture 4 Learning (1) (PDF)
• Lecture 5 Learning (2) (PDF)
• Lecture 6 Learning (3) (PDF)
• Lecture 7 Learning (4) (PDF)
• Lecture 8 Learning (5) (PDF)
• Lecture 9 Multilayer Perceptron (1): Model (PDF)
• Lecture 10 Multilayer Perceptron (2): Learning (PDF)
• Lecture 11 Multilayer Perceptron (3): Back Propagation (PDF)
• Lecture 12 Multilayer Peceptron (4): Implementation (PDF)
• Lecture 13 Multilayer Peceptron (5): Details (PDF)
• Lecture 14 Multiplayer Peceptron (6): Model Selection (PDF)
• Lecture 15 Classification (1) (PDF)
• Lecture 16 Classification (2) (PDF)
• Lecture 17 Support Vector Machine (1): Basics (PDF)
• Lecture 18 Support Vector Machine (2): Nonseparable case (PDF)
• Lecutre 19 Support Vector Machine (3): Kernel (PDF)
• Lecture 20 clustering (1): Kmeans algorithm (PDF)
• Lecture 21 clustering (2): distortion measures (PDF)
• Lecture 22 clustering (3): Self-Organization Map (PDF)
• Lecture 23 clustering (4): prob density function estimation (PDF)
• Lecture 24 Radial basis function (1) (PDF)
• Lecture 25 Radial basis function (2) (PDF)
• Lecture 26 Model (1): time series analysis (PDF)
• Lecture 27 Model (2): system identification and control (PDF)
• Lecture 28 Model (3): expert system (PDF)
• Lecture 29 Fuzzy Systems (1) (PDF)
• Lecture 30 Fuzzy Systems (2) (PDF)
• Lecture 31 Fuzzy Systems (3) (PDF)
• Lecture 32 Fuzzy Systems (4) (PDF)
• Lecture 33 Fuzzy Logic Control (1) (PDF)
• Lecture 34 Fuzzy Logic Control (2) (PDF)
• Lecture 35 Fuzzy Logic Control (3) (PDF)
• Lecture 36 Genetic Algorithm (1) (PDF)
• Lecture 37 Genetic Algorithm (2) (PDF)
• Lecture 38 Mixture of Expert Neural Network (PDF)
• Lecture 39 Hopfield Network (PDF)

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