Objectives
Outcomes
Unit – I
Perceptron Architecture- Single-Neuron Perceptron- Multi-Neuron Perceptron-
Unit – II
Perceptron Learning Rule- Constructing Learning Rules- Training Multiple-Neuron Perceptrons.
Unit – III
Simple Associative Networks- Unsupervised Hebb Rule- Hebb Rule with Decay-Instar Rule-Outstar Rule- Kohonen Rule.
Unit – IV
Adaline Network- Madaline Network -Mean Square Error- LMS Algorithm- Back Propagationa Neural networks – Hopfield Networks
Unit – V
Adaptive Filtering- Adaptive Noise Cancellation- Forecasting – Neural control applications – Character recognition.