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A Parameter-Changing and Complex-Valued Zeroing Neural-Network for Finding Solution of Time-Varying Complex Linear Matrix Equations in Finite Time | IEEE Journals & Magazine | IEEE Xplore

A Parameter-Changing and Complex-Valued Zeroing Neural-Network for Finding Solution of Time-Varying Complex Linear Matrix Equations in Finite Time


Abstract:

For solving complex-valued linear matrix equations with time-varying coefficients (CV-LME-TVC) in the complex field, this article proposes a parameter-changing and comple...Show More

Abstract:

For solving complex-valued linear matrix equations with time-varying coefficients (CV-LME-TVC) in the complex field, this article proposes a parameter-changing and complex-valued zeroing neural network (PC-CVZNN) model through integrating a new parameter-changing function. As compared to previous complex-valued zeroing neural networks (CVZNNs) with fixed parameters and existing parameter-changing functions, the PC-CVZNN model can achieve superior performance due to the accelerated role of the new parameter-changing function. In parts of theoretical analysis, we take advantage of Lyapunov methodology to prove that the proposed PC-CVZNN model can acquire the global and super-exponential convergence when the linear activation function is adopted, and even acquire super finite-time convergence when the new sign-bi-power activation function and its modified one are used. In parts of numerical comparison experiments, it is shown that the PC-CVZNN model possesses faster convergence rate than fixed-parameter CVZNN models and other analogy neural networks with parameter-changing function, when applied to finding the solution of CV-LME-TVC. Importantly, an application of the proposed method to the mobile manipulator control provides the potential practical value of the PC-CVZNN model in the industrial field.
Published in: IEEE Transactions on Industrial Informatics ( Volume: 17, Issue: 10, October 2021)
Page(s): 6634 - 6643
Date of Publication: 05 January 2021

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