CSVTU B.E. VIII Semester Computer Science Engineering Neural Network and Fuzzy Logic Syllabus
CHHATTISGARH SWAMI VIVEKANAND TECHNICAL UNIVERSITY, BHILAI (C.G.)
Semester: VIII Branch: Computer Science & Engg.
Subject: Neural Network and Fuzzy Logic.
UNIT-I Introduction to Artificial Neural Networks:
Elementary Neurophysiology, Models of a Neuron, Neural Networks viewed as directed graphs,
Feedback, from neurons to ANN, Artificial Intelligence and Neural Networks; Network Architectures,
Single-layered Feed forward Networks, Multi-layered Feed forward Networks,
Recurrent Networks, Topologies.
UNIT-II Learning and Training :
Activation and Synaptic Dynamics, Hebbian, Memory based, Competitive, Error-Correction
Learning, Credit Assignment Problem: Supervised and Unsupervised learning, Memory models,
Stability and Convergence, Recall and Adaptation.
UNIT-III A Survey of Neural Network Models :
Single-layered Perceptron – least mean square algorithm, Multi-layered Perceptrons – Back
propagation Algorithm, XOR – Problem, The generalized Delta rule, BPN Applications, Adalines
and Madalines – Algorithm and applications.
UNIT-IV Applications :
Talking Network and Phonetic typewriter : Speech Generation and Speech recognition,
Neocognitron – Character Recognition and Handwritten Digit recognition, Pattern Recognition
UNIT-V Neural Fuzzy Systems :
Introduction to Fuzzy sets, operations, relations, Examples of Fuzzy logic, Defuzzification,
Fuzzy Associative memories, Fuzziness in neural networks and examples ,
1. Artificial Neural Networks by B. Yagna Narayan, PHI
2. Neural Networks Fuzzy Logic & Genetic Alogrithms by Rajshekaran & Pai, Prentice Hall
1.Neural Networks by James A. Freeman and David M. Strapetuns, Prentice Hall,.
3. Neural Network & Fuzzy System by Bart Kosko, PHI.
4. Neural Network Design by Hagan Demuth Deale Vikas Publication House