Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Issue title: Proceedings of the International Conference on Mechatronics and Information Technology (ICMIT 2005, ICMIT 2007)
Article type: Research Article
Authors: Sasaki, Minorua; * | Kuribayashi, Takumia | Ito, Satoshia | Inoue, Yoshihirob
Affiliations: [a] Department of Human and Information Systems Engineering, Gifu University, Gifu, Japan | [b] Department of Mechanical and Systems Engineering, Gifu University, Gifu, Japan
Correspondence: [*] Corresponding author. Department of Human and Information Systems Engineering, Gifu University, Gifu, Japan 1-1 Yanagido, Gifu, Japan. Tel.: +81 58 293 2541; Fax: +81 58 230 1892; E-mail: sasaki@gifu-u.ac.jp
Abstract: In this paper an active random noise control using adaptive learning rate neural networks with an immune feedback law is presented. The adaptive learning rate strategy increases the learning rate by a small constant if the current partial derivative of the objective function with respect to the weight and the exponential average of the previous derivatives have the same sign, otherwise the learning rate is decreased in proportion to its value. The use of an adaptive learning rate attempts to keep the learning step size as large as possible without inducing oscillation. In the proposed method, because an immune feedback law is changing the learning rate of the neural networks individually and adaptively, it is expected that the neural cost function will reach its minimum rapidly, resulting in a reduced training time. Numerical simulations and experiments of active random noise control with the transfer function of the error path will be performed to validate the convergence properties of the method. Control results show that the adaptive learning rate neural network control structure can outperform linear controllers and conventional neural network controllers for active random noise control.
Keywords: Active noise control, random noise, immune feedback law, adaptive filtering algorithm
DOI: 10.3233/JAE-2011-1341
Journal: International Journal of Applied Electromagnetics and Mechanics, vol. 36, no. 1-2, pp. 29-39, 2011
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl