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- W2625128551 abstract "In this study, we investigate the control performance of an adaptive controller using multilayer hypercomplex-valued neural networks, such as complex, hyperbolic, bicomplex and quaternion neural networks. The control system is a direct controller whereby the control input of a plant is synthesized online using the multilayer hypercomplex-valued neural network to track the plant output to the desired output generated by a reference model. Computational experiments to control a multiple-input and multiple-output discrete-time nonlinear plant are conducted to evaluate the capability and characteristics of the hypercomplex–valued neural network–based direct adaptive controller. Experimental results show the feasibility and effectiveness of the proposed controller." @default.
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- W2625128551 date "2016-09-01" @default.
- W2625128551 modified "2023-09-26" @default.
- W2625128551 title "Remarks on Hypercomplex-Valued Neural Network-Based Direct Adaptive Controller" @default.
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- W2625128551 doi "https://doi.org/10.1109/icmssp.2016.027" @default.
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