Title :
Sparse Representation and Associative Learning in Multisensory Integration
Author_Institution :
Dept. of Comput. Sci. & Eng., Shanghai Jiao Tong Univ.
Abstract :
In this paper, we discuss multisensory information representation and associative learning in multimodal integration. First, we provide a brief overview of anatomical structure and neural information pathways of multimodal cortexes. Then we formulate the multimodal integration problem into a framework of statistical learning. The associative learning algorithm is proposed to adapt the representation matrix and the sparseness of representation is also adapted in the statistical learning model
Keywords :
learning (artificial intelligence); neural nets; statistical analysis; anatomical structure; associative learning algorithm; multimodal cortexes; multimodal integration; multisensory information representation; neural information pathways; sparse representation; statistical learning model; Anatomical structure; Biological neural networks; Inference algorithms; Information processing; Information representation; Lips; Redundancy; Shape; Signal resolution; Statistical learning;
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.2005.1614942
