Cortical Algorithms

Abstract

Computational models based on the structural and functional properties of the human brain have seen impressive gains since the mid-1980s, owing to significant discoveries in neuroscience and advancements in computing technology. Among these models, cortical algorithms (CAs) have emerged as a biologically inspired approach, modeled after the human visual cortex, which stores sequences of patterns in an invariant form and which recalls those patterns autoassociatively. This chapter details the structure and mathematical formulation of CA. We then present a case study of CA generalization accuracy in identifying isolated Arabic speech using an entropy-based weight update.