Title :
Sparse Representation and Synaptic Adaptation of the Visual Sensory System
Author :
Zhang, Liqing ; Ma, Libo ; Yang, Wenlu ; Xia, Bin
Author_Institution :
Dept. of Comput. Sci. & Eng., Shanghai Jiao Tong Univ.
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
Keywords :
learning (artificial intelligence); neural nets; neurophysiology; statistical analysis; visual perception; generative statistical model; learning algorithm; sparse representation; synaptic adaptation; visual neural information; visual sensory system; Biological neural networks; Brain modeling; Codes; Computer networks; Computer simulation; Neurons; Neuroscience; Parameter estimation; Probability density function; Statistics;
Conference_Titel :
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9422-4
DOI :
10.1109/ICNNB.2005.1615008
