Simple Hebbian learning rules and correlated inputs

This lecture introduces Simple Hebbian learning rules and correlated inputs, explaining how weight vectors converge to identical values. Through examples, it demonstrates how correlated input units dominate the activity of the output neuron, causing their weights to always increase. The instructor also discusses Hebbian Learning rate model and covariance rule.