Neural Network

Unit-1 Basics of Artificial Neural Networks

A neuron
Biological Neural Network
Artificial Neural Network
Neural Network Topology
Models of Neuron
Activation Functions
Properties / Characteristics/ Benefits of Neural Network

Unit-2 Learning in Neural Network

Activation and Synaptic Dynamics
Training Neural Network
Learning and its types
Basic Learning Laws
Stability and convergence
Recall in Neural Network

Unit-3: Feed Forward Neural Networks

Recognition Tasks performed by Feed-Forward Networks:

• Pattern Association Problem
• Pattern Classification Problem
• Pattern Mapping
• Pattern Recognition
• Pattern Association

Generalization
Perceptron, Perceptron Learning Law
Linear Separability and XOR problem

Multi-layer Feed Forward Networks
Back-propagation 

Unit 4- Feedback Neural Networks 
Competitive Learning Neural Network
Stochastic Networks
Boltzmann Machine
Hopefield Neural Network
Simulated Annealing 
Associative Memory 
Tasks performed by Competitive Nets: 
Pattern Clustering, Pattern Storage 

UNIT 5- Hybrid Neural Networks 
Counter Propagation
Adaptive Resonance Theory
Neocognitron
Stability-Plasticity Dilemma
Application of ANN