Global Gravitational Search Algorithm-Aided Kalman Filter Design for Volterra-Based Nonlinear System Identification-Reference-Cited by-同舟云学术

Global Gravitational Search Algorithm-Aided Kalman Filter Design for Volterra-Based Nonlinear System Identification

Published:2020-11-20 Issue:5 Volume:40 Page:2302-2334
ISSN:0278-081X
Container-title:Circuits, Systems, and Signal Processing
language:en
Short-container-title:Circuits Syst Signal Process

Author:

Janjanam Lakshminarayana^ORCID,Saha Suman Kumar,Kar Rajib,Mandal Durbadal

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Signal Processing

Link

http://link.springer.com/content/pdf/10.1007/s00034-020-01593-6.pdf

Reference54 articles.

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2. M. Ahmeid, M. Armstrong, S. Gadoue, M. Al-Greer, P. Missailidis, Real-time parameter estimation of DC-DC converters using a self-tuned Kalman Filter. IEEE Trans. Power Electron. 32(7), 5666–5674 (2017)

3. A. Anita, Yadav, AEFA: artificial electric field algorithm for global optimisation. Swarm Evol. Comput. 48, 93–108 (2019)

4. K. Batselier, N. Wong, Matrix output extension of the tensor network Kalman filter with an application in MIMO Volterra system identification. Automatica 95, 413–418 (2018)

5. K. Batselier, Z. Chen, N. Wonga, A tensor network Kalman filter with an application in recursive MIMO Volterra system identification. Automatica 84, 17–25 (2017)

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