CSVTU BE VIII Semester IT Neural Network and Fuzzy Logic Syllabus
CHHATTISGARH SWAMI VIVEKANAND TECHNICAL UNIVERSITY, BHILAI (C.G.)
Semester:VIII Branch: Information Technology
Subject: Neural Network and Fuzzy Logic
UNIT-1 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 Feedforward Networks,
Recurrent Networks, Topologies.
UNIT-2 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-3 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.
Talking Network and Phonetic typewriter: Speech Generation and Speech recognition,
Neocognitron – Character Recognition and Handwritten Digit recognition, Pattern Recognition
UNIT-5 Neural Fuzzy Systems:
Introduction to Fuzzy sets, operations, relations, Examples of Fuzzy logic, Defuzzyfication,
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