DocumentCode :
2494830
Title :
An associative memory system for incremental learning and temporal sequence
Author :
Shen, Furao ; Yu, Hui ; Kasai, Wataru ; Hasegawa, Osamu
Author_Institution :
State Key Lab. for Novel Software Technol., Nanjing Univ., Nanjing, China
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
8
Abstract :
An associative memory (AM) system is proposed to realize incremental learning and temporal sequence learning. The proposed system is constructed with three layer networks: The input layer inputs key vectors, response vectors, and the associative relation between vectors. The memory layer stores input vectors incrementally to corresponding classes. The associative layer builds associative relations between classes. The proposed method can incrementally learn key vectors and response vectors; store and recall both static information and temporal sequence information; and recall information from incomplete or noise-polluted inputs. Experiments using binary data, real-value data, and temporal sequences show that the proposed method works well.
Keywords :
associative processing; content-addressable storage; learning (artificial intelligence); associative memory system; incremental learning; temporal sequence learning; Associative memory; Context; Humans; Indexes; Prototypes; Topology; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location :
Barcelona
ISSN :
1098-7576
Print_ISBN :
978-1-4244-6916-1
Type :
conf
DOI :
10.1109/IJCNN.2010.5596780
Filename :
5596780
Link To Document :
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