Analyzing Hebbian Learning Rule

This lecture delves into the analysis of Hebbian learning rules, focusing on rate-based Hebbian learning and the application of Taylor expansion to determine the change of weights based on pre- and post-synaptic firing rates. It also covers Hebbian learning rate models, Oja's rule, post-synaptic and pre-synaptic thresholds, and the covariance rule. The presentation includes a discussion on the covariance matrix and the growth of weight vectors in the context of Hebbian learning.