Question

Whats true for sparse encoding 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 posed to me in examination.

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

Answer 1

The correct answer is (a) logical And & Or operations are used for input output relations

For explanation I would say: sparse encoding learning employs Logical And & Or operations are used for input output relations.