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- W2022158576 abstract "A special kind of neural dynamics, termed Zhang dynamics ZD, is proposed, generalized and investigated for the online solution of time-varying scalar-valued nonlinear inequalities by following Zhang et al.’s design method. The continuous-time ZD CTZD model based on an exponent-type design formula can be guaranteed to exponentially converge to the time-varying solution set of the problem in an error-free manner. For potential hardware implementation on digital circuits, the corresponding discrete-time ZD DTZD model is generated through the well-known Euler forward difference rule. Newton-type algorithm is also developed for comparison purposes. In addition, the simplified CTZD S-CTZD and DTZD S-DTZD models are developed for solving static scalar-valued nonlinear inequalities. Numerical simulative examples further demonstrate and verify the efficacy of the ZD models for solving time-varying and static scalar-valued nonlinear inequalities. Besides, the DTZD model possesses the lower complexity and higher accuracy, as compared with the Newton-type algorithm." @default.
- W2022158576 created "2016-06-24" @default.
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- W2022158576 date "2013-02-22" @default.
- W2022158576 modified "2023-10-08" @default.
- W2022158576 title "Solving time-varying nonlinear inequalities using continuous and discrete-time Zhang dynamics" @default.
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- W2022158576 doi "https://doi.org/10.1080/00207160.2012.750305" @default.
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