Control of wind turbines using memory-based method

Author:

Song Y.D

Publisher

Elsevier BV

Subject

Mechanical Engineering,Renewable Energy, Sustainability and the Environment,Civil and Structural Engineering

Reference20 articles.

1. C.G. Atkeson, D.J. Reinkensmeyer, Using associate content-addressable memories to control robots, W.T. Miller, R.S. Sutton, P.J. Werbos (Eds.), Neural Networks for Control, Multiscience Press, Inc., 1992, pp. 255–285.

2. G. Cybenko, Approximation by superposition of a sigmoidal function, Math. Control Signals Systems (2) (1989) 303–314.

3. E. Fix, J.L. Hodges Jr., Discriminatory analysis, non-parameteric regression: consistency properties, Technical Report No. 4, USAF School Aviation Medicine Randolph Field, TX AF- 41-(128)-31, 1951.

4. Atmospheric predictability as revealed by naturally occurring analogues;Lorenz;J. Atmos. Sci.,1969

5. A.W. Moore, Efficient memory-based learning for robot control, Ph.D. Thesis, Technical Report 229, Computer Laboratory, University of Cambridge, October 1990.

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