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ARX RBFN Model for Nonlinear Dynamical Systems Identification", SICE Journal of
Control, Measurement, and System Integration, Vol.9, No.2, pp.70-77, 2016.
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Network Based Adaptive Predictive Control for Nonlinear Systems", IEEJ Trans. on
Electrical and Electronic Engineering, Vol.11, No.1, pp.83-90, 2016.
- M.A. Jami'in, I. Sutrisno and J. Hu, "Maximum Power Tracking Control for a Wind Energy
Conversion System Based on a Quasi-ARX Neural Network Model", IEEJ Trans. on
Electrical and Electronic Engineering, Vol.10, No.4, pp.368-375, 2015.
- I. Sutrisno, M.A. Jami'in and J. Hu, "An Improved Elman Neural Network Controller
Based on Quasi-ARX Neural Network for Nonlinear Systems", IEEJ Trans. on
Electrical and Electronic Engineering, Vol.9, No.5, pp.494-501, 2014.
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Based on Quasi-ARX Model", IEEJ Trans. on
Electrical and Electronic Engineering, Vol.7, No.4, pp.390-396, 2012.
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SVR and GA Approach", IEICE Trans. on Fundamentals of Electronics, communications
and Computer Sciences, Vol.E95-A, No.5, pp.876-883, 2012.
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SVR and GA Approach", onlinear Theory and its Applications (NOLTA), IEICE,
Vol.2, No.2, pp.165-179, 2011.
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Mechanism to Adaptive Control of Nonlinear Systems", SICE Journal of
Control, Measurement, and System Integration, Vol.3, No.4, 2010.
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Quasi-ARMAX Approach to the Modeling of
Nonlinear Systems ", International
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Neurofuzzy Approach to Fault Detection
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K.Hirasawa, " KDI-Based Robust Fault
Detection in Presence of Nonlinear
Undermodeling", Trans. of the Society of
Instrument and Control Engineering,
Vol.35, No.2, pp.200-207,1999
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K.Hirasawa, " A Hybrid Quasi-ARMAX
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