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Please use this identifier to cite or link to this item: http://scholars.ntou.edu.tw/handle/123456789/18129
Title: Effects of using different neural network structures and cost functions in locomotion control
Authors: Jih-Gau Juang 
Keywords: neural networks;Cost function;Intelligent networks;Legged locomotion;Artificial intelligence;Backpropagation;leg;Artificial neural networks;Robots;Learning
Issue Date: 28-Jun-2000
Publisher: IEEE
Journal Volume: 5
Start page/Pages: 3523-3527
Conference: Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334)
Chicago, IL, USA
Abstract: 
Effects of using different neural network structures and cost functions in locomotion control are investigated. Simulations focus on refinement and a thorough understanding of an artificial intelligent learning scheme. This scheme uses a neural network controller with backpropagation through time learning rule. Through learning, the controller can generate locomotion trajectory along a pre-defined path. Different issues regarding the scheme have been examined. They include the effects of using different numbers of hidden units and the effects of using only position parameters in the cost function.
URI: http://scholars.ntou.edu.tw/handle/123456789/18129
ISBN: 0-7803-5519-9
ISSN: 0743-1619
DOI: 10.1109/ACC.2000.879225
Appears in Collections:通訊與導航工程學系

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