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arXiv 2602.12467math.DS
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具有分布式记忆的状态依赖延迟微分方程

State dependent delay differential equations with distributed memory

Ankara University(安卡拉大学);Abbottabad University of Science and Technology(阿伯塔巴德科学与技术大学)

Taylan Demir, Niaz Ali Shah

AI总结:

本文研究了具有分布式记忆的状态依赖延迟微分方程,通过分析逻辑模型展示了高阶记忆核可能引发振荡动力学,并建立了稳定性与分支分析的严格框架。

摘要:

我们研究了具有分布式记忆的状态依赖延迟微分方程,结合了离散的状态依赖延迟和一种卷积型记忆算子。在延迟、核函数和非线性项满足Lipschitz型假设的情况下,我们利用Banach空间中的不动点论证方法,建立了局部良好设定性。分布式记忆算子被证明是局部Lipschitz的,从而保证了存在性和唯一性。作为基准,我们分析了一个具有阶数为二的Gamma分布记忆核的逻辑模型。卷积项被减少为有限维形式,从而得到显式的特征方程和闭合形式的Hopf分支阈值和频率。结果表明,高阶记忆核可能引发振荡动力学,不同于纯指数记忆,并为具有状态依赖记忆的延迟系统提供了严格稳定性与分支分析的框架。

英文摘要:

We investigate state dependent delay differential equations with distributed memory, combining discrete state dependent delays and a convolution type memory operator. Under Lipschitz type assumptions on the delay, kernel, and nonlinear term, we establish local well posedness using a fixed point argument in a Banach space of histories. The distributed memory operator is shown to be locally Lipschitz, ensuring existence and uniqueness. As a benchmark, we analyze a logistic model with a Gamma distributed memory kernel of order two. The convolution term is reduced to a finite dimensional form, yielding an explicit characteristic equation and closed form Hopf bifurcation threshold and frequency. The results show that higher order memory kernels may induce oscillatory dynamics, unlike purely exponential memory, and provide a rigorous framework for stability and bifurcation analysis in delay systems with state dependent memory.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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