NDLI: New skill learning paradigm using various kinds of neurons

Content Provider	IEEE Xplore Digital Library
Author	Tae-Dok Eom Sung-Woo Kim Changkyu Choi Ju-Jang Lee
Copyright Year	1996
Description	Author affiliation: Dept. of Electr. Eng., Korea Adv. Inst. of Sci. & Technol., Taejon, South Korea (Tae-Dok Eom)
Abstract	Modeled from human neurons, various types of artificial neurons are developed and applied to control algorithm. In this paper, the weights and structure of feedforward neural network controller are updated using new skill learning paradigm which consists of supervisory controller, chaotic neuron filter and associative memory. The pattern of system nonlinearity along the desired path is extracted while supervisory controller guarantees stability in the sense of the boundedness of tracking error. Next the pattern is divided into small segments and encoded to bipolar codes depending on the existence of critical points. Comparing the encoded pattern with pre-stored neural parameters and pattern pairs through associative memory, the most similar one is obtained. Also, chaotic neuron filter is used to add perturbation to neural parameters when the training of feedforward neural network is not successful with the pre-stored parameters. Finally the memory is updated with new successful parameters and pattern pairs. Simulation is performed for simple two-link robot in case of the slight modification of desired trajectory.
Starting Page	1157
Ending Page	1164
File Size	624345
Page Count	8
File Format	PDF
ISBN	078033213X
DOI	10.1109/IROS.1996.568965
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-11-08
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neurons Neural networks Feedforward neural networks Chaos Filters Associative memory Humans Artificial neural networks Nonlinear control systems Control systems
Content Type	Text
Resource Type	Article

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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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