DocumentCode :
2777369
Title :
Chaotic Quaternionic Associative Memory
Author :
Osana, Yuko
Author_Institution :
Sch. of Comput. Sci., Tokyo Univ. of Technol., Tokyo, Japan
fYear :
2012
fDate :
10-15 June 2012
Firstpage :
1
Lastpage :
8
Abstract :
In this paper, we propose a chaotic quaternionic neuron model and a Chaotic Quaternionic Associative Memory (CQAM). The proposed chaotic quaternionic neuron model is based on the chaotic neuron model and the quaternionic neuron model. In the chaotic quaternionic neuron model, if the parameters are set appropriately, chaotic response can be generated. The proposed Chaotic Quaternionic Associative Memory is composed of chaotic quaternionic neuron models, and has a structure which is similar to the Hopfield network. In the proposed Chaotic Quaternionic Associative Memory, plural patterns are given to the network as external inputs at the same time, each pattern can be recalled separately. The proposed Chaotic Quaternionic Associative Memory makes use of the dynamic association ability of the chaotic quaternionic neuron model in order to realize pattern separation. We carried out a series of computer experiments and confirmed that (1) the chaotic quaternionic neuron can generate chaotic response when the parameters are set appropriately and (2) the pattern separation can be realized in the Chaotic Quaternionic Associative Memory.
Keywords :
Hopfield neural nets; chaos; content-addressable storage; number theory; CQAM; Hopfield network; chaotic quaternionic associative memory; chaotic quaternionic neuron model; chaotic response generation; dynamic association ability; pattern separation; Birds; Whales;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), The 2012 International Joint Conference on
Conference_Location :
Brisbane, QLD
ISSN :
2161-4393
Print_ISBN :
978-1-4673-1488-6
Electronic_ISBN :
2161-4393
Type :
conf
DOI :
10.1109/IJCNN.2012.6252775
Filename :
6252775
Link To Document :
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