Novel insights on distributed delayed flexible impulsive control for mixed delay complex-valued neural networks

Volume 41, Issue 3, pp 307--321 https://dx.doi.org/10.22436/jmcs.041.03.02

Publication Date: October 29, 2025 Submission Date: June 24, 2025 Revision Date: July 31, 2025 Accteptance Date: August 21, 2025

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Authors

K. P. Lakshmi - Department of Mathematics, Amrita School of Physical Sciences, Kochi, Amrita Vishwa Vidyapeetham, India. T. Senthilkumar - Department of Mathematics, Amrita School of Physical Sciences, Kochi, Amrita Vishwa Vidyapeetham, India. A. Vinodkumar - Department of Mathematics, Amrita School of Physical Sciences, Coimbatore, Amrita Vishwa Vidyapeetham, India. J. Alzabut - Department of Mathematics and General Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia. - Department of Industrial Engineering, OSTIM Technical University, 06374, Ankara, Turkey. M. Tounsi - Computer Science Department, Prince Sultan University, Riyadh 11586, Saudi Arabia.

Abstract

This research investigates novel synchronization criteria for uncertain mixed-delay complex-valued neural networks (CVNNs) using distributed delayed flexible impulsive control (DDFIC). To cope with the mixed delays, we offer a novel distributed delayed flexible impulsive differential inequality that incorporates the average impulsive distributed delay and average impulsive interval. In addition, new synchronization requirements for linear matrix inequalities (LMIs) are developed for the proposed CVNNs using the Lyapunov function and Jensen's inequality. The DDFIC gains are also determined by solving the LMIs. Lastly, we include simulation examples to exemplify the proposed criteria, and to illustrate the effectiveness of the DDFIC through diagrammatic representations.

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Keywords

• Mixed delay
• distributed delayed flexible impulsive control
• complex-valued neural networks
• exponential synchronization

MSC

•  34K41
•  93C27
•  93D23

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