Syllabus of Anna University Coimbatore B.Tech IT Neural Networks


This resource provides you the information about syllabus of B.Tech IT Main Neural Networks in Anna University of Technology Coimbatore

University : Anna University of Technology Coimbatore
Discipline : Information Technology
Degree : Bachelor of Technology (IT)
Regular : Full time

Subject Title: Neural Networks

UNIT – I INTRODUCTION TO NEURAL NETWORKS
Introduction, Humans and Computers, Organization of the Brain, Biological
Neuron, Biological and Artificial Neuron Models, Characteristics of ANN,
McCulloch-Pitts Model, Historical Developments, Potential Applications of ANN.

UNIT – II ESSENTIALS OF ARTIFICIAL NEURAL NETWORKS
Artificial Neuron Model, Operations of Artificial Neuron, Types of Neuron
Activation Function, ANN Architectures, Classification Taxonomy of ANN –
Connectivity, Learning Strategy (Supervised, Unsupervised, Reinforcement),
Learning Rules.

UNIT – III SINGLE LAYER FEED FORWARD NETWORKS
Introduction, Perceptron Models: Discrete, Continuous and Multi-Category,
Training Algorithms: Discrete and Continuous Perceptron Networks, Limitations
of the Perceptron Model.

UNIT – IVI MULTI- LAYER FEED FORWARD NETWORKS
Credit Assignment Problem, Generalized Delta Rule, Derivation of
Backpropagation (BP) Training, Summary of Backpropagation Algorithm,
Kolmogorov Theorem, Learning Difficulties and Improvements.

UNIT - V ASSOCIATIVE MEMORIES
Paradigms of Associative Memory, Pattern Mathematics, Hebbian Learning,
General Concepts of Associative Memory, Bidirectional Associative Memory
(BAM) Architecture, BAM Training Algorithms: Storage and Recall Algorithm,
BAM Energy Function.
Architecture of Hopfield Network: Discrete and Continuous versions, Storage and
Recall Algorithm, Stability Analysis. Neural network applications: Process
identification, control, faultdiagnosis.

REFERENCES
1. Laurene Fausett, "Fundamentals of Neural Networks" , Pearson Education,
2004..
2. Simon Haykin, "Neural Networks- A comprehensive foundation", Pearson
Education, 2003.
3. S.N.Sivanandam, S.Sumathi,S. N. Deepa "Introduction to Neural Networks
using MATLAB 6.0", TATA Mc Graw Hill, 2006.
4. S. Rajasekharan and G. A. Vijayalakshmi pai, "Neural Networks, Fuzzy logic,
Genetic algorithms: synthesis and applications", PHI Publication, 2004.
4. Timothy J. Ross, " Fuzzy Logic With Engineering Applications", Tata McGraw-
Hill Inc. 2000


Reference: www.annauniv.ac.in


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