Course contents

Foundations : Stochastic processes; Principal Component Analysis; Learning theory; Generalization and Regularization; Simulated Annealing

Fuzzy Sets; Chaos theory; Evolutionary algorithms and genetic programming

Methodologies : Neural networks architectures for complex pattern recognition tasks - Fuzzy neural networks and chaos in neural networks

Applications : Optimization; Control systems; Speech systems; Image processing; Natural language processing and decision making

Seminar Topics

• Genetic Algorithms
• Dynamic programming
• Self Organizing Maps
• Support Vector Mechine
• Boltzmann Machine
• Fuzzy Filtered Neural Network and Appln: Plasma Spectrum Analysis, Hand Written Numeral Recognition

References

• Neuro Fuzzy & Soft Computing - J.-S.R.Jang, C.-T.Sun, E.mizutani, Pearson Education
• Digital Neural Network - S.Y.Kung, Prentice Hall International Inc.
• Spiking Neural Networks - Wulfram Gerstner, Wenner Kristler, Cambridge University Press.
• Neural Networks and Fuzzy Systems: Dynamical Systems Application to Machine Intelligence - Bart Kosko, Prentice Hall, 1992.