Syllabus of Andhra University BTech Computer Science Engineering - CSE 4.2.3 - Neural Networks & Fuzzy Systems (Elective II)

Fourth year - Second Semester

Instruction: 3 Periods & 1 Tut /week
Univ. Exam : 3 Hours

Sessional Marks: 30
Univ-Exam-Marks:70

1. Neural Networks and Fuzzy Systems

Neural and Fuzzy Machine Intelligence, Fuzziness as Multivalence, The Dynamical-Systems Approach to Machine Intelligence, Intelligent Behavior as Adaptive Model- Free Estimation.

2. Neural Dynamics I: Activations and Signals

Neurons as Functions, Signal Monotonicity, Biological Activations and Signals, Neuron Fields,Neuronal Dynamical Systems, Common Signal Functions, Pulse-Coded Signal Functions.

3. Neuronal Dynamics II: Activation Models

Neuronal Dynamical Systems, Additive Neuronal Dynamics, Additive Neuronal Feedback, Additive Bivalent Models, BAM Connection Matrices, Additive Dynamic and the Noise-Saturation Dilemma, General Neuronal Activations: Cohen-Grossberg and Multiplicative Models.

4. Synaptic Dynamics I: Unsupervised Learning

Learning as Encoding, Change, and Quantization, Four Unsupervised Learning Laws, Probability Spaces and Random Processes, Stochastic Unsupervised Learning and Stochastic Equilibrium, Signal Hebbian Learning, Competitive Learning, Differential Hebbian Learning, Differential Competitive Learning.

5. Synaptic Dynamics II: Supervised Learning

Supervised Function Estimation, Supervised Learning as Operant Conditioning, Supervised Learning as Stochastic Pattern Learning with known Class Memberships, Supervised Learning as stochastic Approximation, The Back propagation Algorithm.

6. Fuzziness Versus Probability

Fuzzy Sets and Systems, Fuzziness in a Probabilistic World, Randomness vs. Ambiguity: Whether vs. How much, The Universe as a Fuzzy Set, The Geometry of Fuzzy Set, The Geometry of Fuzzy Sets: Sets as Points. The Fuzzy Entropy Theorem, The Subsethood theorem. The Entropy- Subsethood Theorem.

7. Fuzzy Associative Memories

Fuzzy Systems as Between-Cube Mappings, Fuzzy and Neural Function Estimators, Fuzzy Hebb FAMs, Adaptive FAMs: Product-Space Clustering in FAM Cells.

Text Book:

Neural Networks & Fuzzy Systems , Bark Kosko, PHI Published in 1994

Reference Books:

1. Fundamentals of Artificial Neural Networks, Mohamad H Hassoum. PHI

2. Neural network Design, Hagan, Demuth and Beale, Vikas Publishing House

3. Fuzzy Set Theory & its Application, .J. Zimmerman Allied Published Ltd.