CSVTU BE VII Semester EEE Neural Network & Fuzzy Logic Syllabus

CSVTU BE VII Semester EEE Neural Network & Fuzzy Logic Syllabus


Semester: VII Branch: EEE/E&T

Subject: Neural Network & Fuzzy Logic

Total Theory Periods: 40 Total Tutorial Periods: 12

Marks in the End Semester Exam : 80

Minimum number of Class tests to be conducted: Two


Introduction to ANS Technology:

Elementary Neurophysiology, Models of a Neuron, Neural Networks

viewed as directed graphs, Feedback, from neurons to ANS, Artificial Intelligence and Neural Networks.


Learning and Training:

Hebbian, Memory based, Competitive, Error-Correction Learning, Credit

Assignment Problem: Supervised and Unsupervised learning, Memory models, Recall and Adaptation.

Network Architectures, Single-layered Feed-forward Networks, Multi-layered Feedforward Networks,

Recurrent Networks, Topologies,


Algoritms for ANN:

Activation and Synaptic Dynamics, Stability and Convergence. 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.



The Traveling salesperson problem, Talking Network and Phonetic typewriter : Speech

Generation and Speech recognition, Character Recognition and Retrieval, Handwritten Digit recognition.


Adaptive Fuzzy Systems:

Introduction to Fuzzy sets and operations, Examples of Fuzzy logic, Fuzzy

Associative memories, Fuzziness in neural networks, Comparison of Fuzzy and neural Truck-Backer upper

control systems.

Names of Text Books:

1. Artificial Neural Networks by B. Yagna Narayan, PHI

2. Neural Network: A Comprehensive Foundation, Haykin, Pearson Education

Names of Reference Books:

1. Neural Networks, Freeman, Pearson Education

2. Fundamentals of Artificial Neural Networks, Hassoun, PHI

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