Sparse Representation and Synaptic Adaptation of the Visual Sensory System

Abstract

This paper investigates the sparse representation of visual neural information and its learning algorithm. First we introduce a generative statistical model for internal representation of visual neural information. Then the neural computing mechanism for representing sensory information in the generative model is discussed, and learning algorithm is developed for training the parameters in the generative model. Finally computer simulations are provided to illustrate the sparseness of the internal representation of the visual information