NDLI: Autonomous learning of novel patterns by utilizing chaotic dynamics

Content Provider	IEEE Xplore Digital Library
Author	Kojima, K. Ito, K.
Copyright Year	1999
Description	Author affiliation: Dept. of Comput. Intelligence & Syst. Sci., Tokyo Inst. of Technol., Yokohama, Japan (Kojima, K.)
Abstract	We propose an autonomous dynamical pattern recognition and learning system which can learn new patterns without any external observer. For realizing the "I don't know" state as a filter, we constructed the network from Lorenz systems. First, we find a parameter which affects the network dynamics from the evolution equation. A series of computer simulations show the dependence of the network dynamics on the parameter. Then we find a critical region of the network dynamics. In this critical region, when the embedded pattern is given to the network, the output pattern of the network immediately goes to the relevant embedded pattern and the state of network reduces to the oscillatory state at once. On the other hand, when no embedded pattern is given to the network, the network state oscillates chaotically. It is considered to be the "I don't know" state. Second, we find a transition rule of the output pattern, that is, the pattern dynamics. This dynamics is approximated with a circle map. Further, we find a power law as a statistical property. It means that the pattern dynamics is intermittent chaos type II or III. Finally, when a Hebb rule is applied to the network under the external stimuli that are unknown patterns, the internal state of the network is inversely bifurcated from the chaotic state to the periodic state according to the progress of learning. By utilizing this bifurcation as an index of the progress of learning, the network can learn new patterns without any external observer. Further the network can learn new patterns without destroying the previous embedded patterns.
Starting Page	284
Ending Page	289
File Size	482527
Page Count	6
File Format	PDF
ISBN	0780357310
ISSN	1062922X
DOI	10.1109/ICSMC.1999.814104
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-10-12
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Chaos Bifurcation Learning systems Equations Robust stability Noise robustness Rabbits Computational intelligence Computer simulation Associative memory
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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