Question

Whats true for principal component learning?

(a) logical And & Or operations are used for input output relations

(b) weight corresponds to minimum & maximum  of units are connected

(c) weights are expressed as linear combination of orthogonal basis vectors

(d) change in weight uses a weighted sum of changes in past input values

The question was asked by my college professor while I was bunking the class.

My query is from Learning Laws in section Activation and Synaptic Dynamics of Neural Networks

Answer 1

Right option is (c) weights are expressed as linear combination of orthogonal basis vectors

To explain: principal component learning involves weights  that are expressed as linear combination of orthogonal basis vectors.