IIT Madras Neural Network

Will you please give here syllabus for Artificial Neural Networks subject of Electronics & Communication Engineering course of IIT Madras?

[Quick Sam]

As you want I am here giving you syllabus for Artificial Neural Networks subject of Electronics & Communication Engineering course of IIT Madras.

Syllabus for Artificial Neural Networks subject:

Introduction and ANN Structure.

Biological neurons and artificial neurons.

Model of an ANN.

Activation functions used in ANNs.

Typical classes of network architectures .

Mathematical Foundations and Learning mechanisms.

Re-visiting vector and matrix algebra.

State-space concepts.

Concepts of optimization.

Error-correction learning.

Mem ory-based learning.

Hebbian learning.

Competitive learning.

Single layer perceptrons.

Structure and learning of perceptrons.

Pattern classifier - introduction and Bayes' classifiers.

Perceptron as a pattern classifier.

Perceptron convergence.

Limitations of a perceptrons.

Feedforward ANN.

Structures of Multi-layer feedforward networks.

Back propagation algorithm.

Back propagation - training and convergence.

Functional approximation with back propagation.

Practical and design issues of back propagation learning.

Radial Basis Function Networks.

Pattern separability and interpolation.

Regularization Theory.

Regularization and RBF networks.

RBF network design and training.

Approximation properties of RBF.

Support Vector machines.

Linear separability and optimal hyperplane.

Determination of optimal hyperplane.

Optimal hyperplane for nonseparable patterns.

Design of an SVM.

Examples of SVM.

Competitive Learning and Self organizing ANN.

General clustering procedures.

Learning Vector Quantization (LVQ).

Competitive learning algorithms and architectures.

Self organizing feature maps.

Properties of feature maps.

Fuzzy Neural Networks.

Neuro-fuzzy systems.

Background of fuzzy sets and logic.

Design of fuzzy stems.

Design of fuzzy ANNs.

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