Modified ZND with Immunity to Periodic Noises for Solving Time-Varying Nonlinear Equations: A Control Perspective

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Abstract 

In this paper, a modified zeroing neurodynamics (MZND) model with immunity to periodic noises is proposed from a control perspective to address time-varying nonlinear equations (TVNE), a common issue in engineering applications. Grounded in the Lyapunov stability theory, this paper provides a thorough assessment of the performance of the MZND model. Through comparative analyses and simulations, the superior performance of the MZND model is validated against existing neurodynamics models. The MZND model stands out for its inherent immunity to periodic noises, a critical feature for enhancing robust in noisy real-world environments. The practical efficacy of the MZND model is exemplified by its application in 3D dynamic sound source location, demonstrating exceptional

 

performance in engineering settings.

Instructions: 

In this paper, a modified zeroing neurodynamics (MZND) model with immunity to periodic noises is proposed from a control perspective to address time-varying nonlinear equations (TVNE), a common issue in engineering applications. Grounded in the Lyapunov stability theory, this paper provides a thorough assessment of the performance of the MZND model. Through comparative analyses and simulations, the superior performance of the MZND model is validated against existing neurodynamics models. The MZND model stands out for its inherent immunity to periodic noises, a critical feature for enhancing robust in noisy real-world environments. The practical efficacy of the MZND model is exemplified by its application in 3D dynamic sound source location, demonstrating exceptional performance in engineering settings.

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