A combined power activation function based convergent factor-variable ZNN model for solving dynamic matrix inversion
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DOI: 10.1016/j.matcom.2022.02.019
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References listed on IDEAS
- Guo, Dongsheng & Zhang, Yunong, 2015. "ZNN for solving online time-varying linear matrix–vector inequality via equality conversion," Applied Mathematics and Computation, Elsevier, vol. 259(C), pages 327-338.
- Zhao, Lv & Jin, Jie & Gong, Jianqiang, 2021. "Robust zeroing neural network for fixed-time kinematic control of wheeled mobile robot in noise-polluted environment," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 185(C), pages 289-307.
- Xiao, Lin & Yi, Qian & Zuo, Qiuyue & He, Yongjun, 2020. "Improved finite-time zeroing neural networks for time-varying complex Sylvester equation solving," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 178(C), pages 246-258.
- Stanimirović, Predrag & Gerontitis, Dimitris & Tzekis, Panagiotis & Behera, Ratikanta & Sahoo, Jajati Keshari, 2021. "Simulation of Varying Parameter Recurrent Neural Network with application to matrix inversion," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 185(C), pages 614-628.
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Cited by:
- Wenrui Yang & Yang Gu & Xia Xie & Chengze Jiang & Zhiyuan Song & Yudong Zhang, 2023. "Bounded Adaptive Function Activated Recurrent Neural Network for Solving the Dynamic QR Factorization," Mathematics, MDPI, vol. 11(10), pages 1-18, May.
- Miao, Peng & Zheng, Yuhua & Li, Shuai, 2024. "A new FXTZNN model for solving TVCS equation and application to pseudo-inverse of a matrix," Applied Mathematics and Computation, Elsevier, vol. 465(C).
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Keywords
Fixed-time convergence; Dynamic matrix inversion (DMI); Combined power activation function (CPAF); Convergent factor-variable zeroing neural networks (CFVZNN); Mobile manipulator;All these keywords.
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