DocumentCode :
2799827
Title :
High performance associative memory neural network
Author :
Wang, Jian ; Mao, Zong-Yuan
Author_Institution :
Coll. of Autom. Sci. & Eng., South China Univ. of Technol., Guangzhou, China
Volume :
2
fYear :
2003
fDate :
8-13 Oct. 2003
Firstpage :
886
Abstract :
In this paper a new associative memory neural network is proposed. Neuron state is a vector. A pattern stored in the network with N neurons consists of N second level patterns with M components. Each pattern is stored in a "pattern loop" which is composed of N links. A link consists of "link state" and "inhibited path", the former is used to store second level pattern, and the later to eliminate spurious pattern. Its storage capacity can be up to (N-1)!; it can completely suppress spurious patterns and permit to input incomplete patterns for recalling; and can recall all or number of the stored patterns which have the minimum Hamming distance with input pattern.
Keywords :
content-addressable storage; neural nets; vectors; Hamming distance; associative memory neural network; incomplete patterns; inhibited path; link state; neuron state; pattern loop; second level pattern; spurious patterns; storage capacity; vectors; Associative memory; Automation; Bidirectional control; Educational institutions; Hamming distance; Information retrieval; Logic; Neural networks; Neurons; Partial response channels;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics, Intelligent Systems and Signal Processing, 2003. Proceedings. 2003 IEEE International Conference on
Print_ISBN :
0-7803-7925-X
Type :
conf
DOI :
10.1109/RISSP.2003.1285704
Filename :
1285704
Link To Document :
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