Volume 1, Issue 2


Volume 1, Issue 2 (December, 2025) – 5 articles
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Table of Contents

Free Access | Research Article | 24 December 2025
Asynchronous Intermittent Event-Triggered Control for a Class of Coupled Stochastic Strict-Feedback Nonlinear Systems
Journal of Nonlinear Dynamics and Applications | Volume 1, Issue 2: 112-126, 2025 | DOI: 10.62762/JNDA.2025.753314
Abstract
This paper investigates a class of coupled stochastic strict-feedback nonlinear systems under asynchronous intermittent event-triggered control (AIETC). Initially, stochastic analysis technique, Lyapunov method and backstepping design method are employed to design the virtual and actual controllers. AIETC is achieved by an auxiliary timer that grants each subsystem its own control and rest time. In the meantime the control input is applied only at the last node of each subsystem. Then, a global Lyapunov function is constructed. By utilizing graph theory, the global exponential ultimate boundedness in mean square of the systems can be obtained and Zeno behavior is eliminated successfully. Fin... More >

Graphical Abstract
Asynchronous Intermittent Event-Triggered Control for a Class of Coupled Stochastic Strict-Feedback Nonlinear Systems
Free Access | Research Article | 16 December 2025
Predefined-Time Synchronization Control of Fractional Cohen-Grossberg Neural Networks with Non-Identical Fractional Orders under Time-Varying Delays
Journal of Nonlinear Dynamics and Applications | Volume 1, Issue 2: 99-111, 2025 | DOI: 10.62762/JNDA.2025.975574
Abstract
In this paper, we study the problem of predefined-time synchronization for distinct-order fractional delayed Cohen-Grossberg neural networks. Fractional-order models are known for their ability to capture memory effects and complex dynamics more accurately than classical integer-order systems. In particular, allowing distinct-order in the drive and response systems provides additional flexibility in modeling. To achieve synchronization, we propose two control strategies that provide sufficient conditions for predefined-time synchronization of the addressed model. These strategies are based on the construction of an appropriate Lyapunov function and the use of fractional calculus properties.... More >

Graphical Abstract
Predefined-Time Synchronization Control of Fractional Cohen-Grossberg Neural Networks with Non-Identical Fractional Orders under Time-Varying Delays
Free Access | Research Article | 10 December 2025
A Nonlinear Dynamical Model of Divorce Due to Extra-Marital Affairs with Long-Distance and Age-Structured Influences
Journal of Nonlinear Dynamics and Applications | Volume 1, Issue 2: 76-98, 2025 | DOI: 10.62762/JNDA.2025.544526
Abstract
This study introduces an age-structured compartmental model that analyzes transitions among stable marriages, long-distance relationships, extra-marital affairs, and divorce. Key behavioral parameters include $\lambda$ (transition to long-distance), $\delta$ (reunification), $\alpha_1$ and $\alpha_2$ (affair formation), $\beta$ (reconciliation), $\gamma$ (affair-driven divorce), and $\mu$ (non-affair divorce). The unmarried women's pool is structured by age, governed by an engagement function $\theta(a)$ and inflow $\Lambda(a)$. A nonlinear differential equation system captures how behavioral mechanisms collectively drive marital dynamics over time. Numerical simulations show that higher $\b... More >

Graphical Abstract
A Nonlinear Dynamical Model of Divorce Due to Extra-Marital Affairs with Long-Distance and Age-Structured Influences
Free Access | Research Article | 19 November 2025
Further Analysis on Preassigned-time Anti-synchronization of Memristive Inertial BAM Neural Networks
Journal of Nonlinear Dynamics and Applications | Volume 1, Issue 2: 63-75, 2025 | DOI: 10.62762/JNDA.2025.473008
Abstract
This paper studies the preassigned time anti-synchronization control problem of a class of bidirectional associative memory (BAM) neural networks with inertia terms and memristor characteristics. By constructing a novel Lyapunov-Krasovskii function and combining it with the latest fixed-time stability theory, it strictly proves the sufficient conditions for the system to achieve anti-synchronization within the preassigned time. Numerical simulations further verified the effectiveness and superiority of the method, especially demonstrating higher accuracy and flexibility when dealing with high-order dynamics and memristor-based systems. More >

Graphical Abstract
Further Analysis on Preassigned-time Anti-synchronization of Memristive Inertial BAM Neural Networks
Free Access | Research Article | 17 November 2025
Semi-Intermittent Control Based Fixed/Predefined-Time Synchronization of Spatiotemporal Memristive Neural Networks
Journal of Nonlinear Dynamics and Applications | Volume 1, Issue 2: 52-62, 2025 | DOI: 10.62762/JNDA.2025.841722
Abstract
This article addresses the fixed-time (FXT) and predefined-time (PDT) synchronization issues of spatiotemporal memristive neural networks (MNNs). First, an aperiodic semi-intermittent control (ASIC) scheme is introduced to reduce the control costs. Then, some novel FXT/PDT synchronization criteria are obtained by using Guass's divergence theorem and by Lyapunov {functional method}. Finally, the feasibility of the theoretical results is confirmed through numerical simulations. More >

Graphical Abstract
Semi-Intermittent Control Based Fixed/Predefined-Time Synchronization of Spatiotemporal Memristive Neural Networks