DocumentCode :
3495374
Title :
Chaotic Complex-valued Multidirectional Associative Memory with variable scaling factor - One-to-many association ability -
Author :
Yoshida, Akio ; Osana, Yuko
Author_Institution :
Sch. of Comput. Sci., Tokyo Univ. of Technol., Hachioji, Japan
fYear :
2011
fDate :
July 31 2011-Aug. 5 2011
Firstpage :
1285
Lastpage :
1292
Abstract :
In this paper, we propose a Chaotic Complex-valued Multidirectional Associative Memory (CCMAM) with variable scale factor which can realize one-to-many associations of M-tuple multi-valued patterns. The proposed model is based on the Multidirectional Associative Memory, and is composed of complex-valued neurons and chaotic complex-valued neurons. In the proposed model, associations of multivalued patterns are realized by using complex-valued neurons, and one-to-many associations are realized by using chaotic complex-valued neurons. Moreover, in the proposed model, the appropriate parameters of chaotic complex-valued neurons can be determined easily than in the original Chaotic Complex-valued Multidirectional Associative Memory. We carried out a series of computer experiments and confirmed that the proposed model has superior one-to-many association ability than that of the conventional model.
Keywords :
chaos; content-addressable storage; neural nets; M-tuple multivalued patterns; chaotic complex-valued multidirectional associative memory; chaotic complex-valued neurons; complex-valued neurons; information processing; neural networks; one-to-many association ability; variable scaling factor;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), The 2011 International Joint Conference on
Conference_Location :
San Jose, CA
ISSN :
2161-4393
Print_ISBN :
978-1-4244-9635-8
Type :
conf
DOI :
10.1109/IJCNN.2011.6033372
Filename :
6033372
Link To Document :
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