A spiking neural network (SNN) includes artificial neurons interconnected by artificial synapses, where the spiking neural network is defined to correspond to one or more numerical matrices, and neurons of the SNN include attributes to inhibit accumulation of potential at the respective neuron responsive to spike messages. Synapses of the SNN have weight values corresponding to one or more numerical matrices. Inputs are provided to the SNN corresponding to a numerical vector. Steady state spiking rates are determined for at least a subset of the neurons and a sparse basis vector is determined based on the steady state spiking rate values.
SPARSE CODING USING NEUROMORPHIC COMPUTING