JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

SOFT COMPUTING TECHNIQUES

M.Tech II Year I Semester (R19)

UNIT - I

Fundamentals of Neural Networks & Feed Forward Networks: Basic Concept of Neural Networks, Human Brain, Models of an Artificial Neuron, Learning Methods, Neural Networks Architectures, Signal Layer Feed Forward Neural Network :The Perceptron Model, Multilayer Feed Forward Neural Network :Architecture of a Back Propagation Network(BPN), The Solution, Backpropagation Learning, Selection of various Parameters in BPN. Application of Back propagation Networks in Pattern Recognition & Image Processing.

UNIT - II

Associative Memories & ART Neural Networks: Basic concepts of Linear Associator, Basic concepts of Dynamical systems, Mathematical Foundation of Discrete-Time Hop field Networks(HPF), Mathematical Foundation of Gradient-Type Hopfield Networks, Transient response of Continuous Time Networks, Applications of HPF in Solution of Optimization Problem: Minimization of the Traveling salesman tour length, Summing networks with digital outputs, Solving Simultaneous Linear Equations, Bidirectional Associative Memory Networks; Cluster Structure, Vector Quantization, Classical ART Networks, Simplified ART Architecture.

UNIT - III

Fuzzy Logic & Systems: Fuzzy sets, Crisp Relations, Fuzzy Relations, Crisp Logic, Predicate Logic, Fuzzy Logic, Fuzzy Rule based system, Defuzzification Methods, Applications: Greg Viot’s Fuzzy Cruise Controller, Air Conditioner Controller.

UNIT - IV

Genetic Algorithms: Basic Concepts of Genetic Algorithms (GA), Biological background, Creation of Offsprings, Working Principle, Encoding, Fitness Function, Reproduction, Inheritance Operators, Cross Over, Inversion and Deletion, Mutation Operator, Bit-wise Operators used in GA, Generational Cycle, Convergence of Genetic Algorithm.

UNIT - V

Hybrid Systems:Types of Hybrid Systems, Neural Networks, Fuzzy Logic, and Genetic Algorithms Hybrid, Genetic Algorithm based BPN: GA Based weight Determination, Fuzzy Back Propagation Networks: LR-type fuzzy numbers, Fuzzy Neuron, Fuzzy BP Architecture, Learning in Fuzzy BPN, Inference by fuzzy BPN.

TEXT BOOKS:

  • 1. Introduction to Artificial Neural Systems - J.M.Zurada, Jaico Publishers
  • 2. Neural Networks, Fuzzy Logic & Genetic Algorithms: Synthesis & Applications - S. Rajasekaran, G. A. Vijayalakshmi Pai, PHI, New Delhi, July 2011.
  • 3. Genetic Algorithms by David E. Gold Berg, Pearson Education India, 2006.
  • 4. Neural Networks & Fuzzy Sytems- Kosko.B., PHI, Delhi,1994.

REFERENCES

  • 1. Artificial Neural Networks - Dr. B. Yagananarayana, PHI, New Delhi, , 1999.
  • 2. An introduction to Genetic Algorithms - Mitchell Melanie, MIT Press, 1998
  • 3. Fuzzy Sets, Uncertainty and Information- Klir G.J. & Folger. T. A., PHI, Delhi, 1993. R19 M.TECH. DIGITAL SYSTEMS AND COMPUTER ELECTRONICS M.TECH.- II YEAR- I SEMESTER DIGITAL SYSTEMS & COMPUTER ELECTRONICS

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