Fast convergence rates and trajectory convergence of a Tikhonov regularized inertial primal–dual dynamical system with time scaling and vanishing damping

IF 2.1 2区 数学 Q1 MATHEMATICS, APPLIED Journal of Computational and Applied Mathematics Pub Date : 2024-11-22 DOI:10.1016/j.cam.2024.116394
Ting Ting Zhu , Rong Hu , Ya Ping Fang
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Abstract

A Tikhonov regularized inertial primal-dual dynamical system with time scaling and vanishing damping is proposed for solving a linearly constrained convex optimization problem in Hilbert spaces. The system under consideration consists of two coupled second order differential equations and its convergence properties depend upon the decaying speed of the product of the time scaling parameter and the Tikhonov regularization parameter (named the rescaled regularization parameter) to zero. When the rescaled regularization parameter converges slowly to zero, the generated primal trajectory converges strongly to the minimal norm solution of the problem under suitable conditions. When the rescaled regularization parameter converges rapidly to zero, the system enjoys fast convergence rates in the primal–dual gap, the feasibility violation, the objective residual, and the gradient norm of the objective function along the trajectory, and the weak convergence of the trajectory to a primal–dual solution of the linearly constrained convex optimization problem. Finally, numerical experiments are performed to illustrate the theoretical findings.
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具有时间缩放和阻尼消失的 Tikhonov 正则化惯性基元二元动力系统的快速收敛率和轨迹收敛性
为解决希尔伯特空间中的线性约束凸优化问题,提出了一种具有时间缩放和阻尼消失的 Tikhonov 正则化惯性原始二元动力系统。所考虑的系统由两个耦合二阶微分方程组成,其收敛特性取决于时间缩放参数与 Tikhonov 正则化参数(称为重标定正则化参数)的乘积衰减为零的速度。当重标定正则化参数缓慢收敛到零时,在合适的条件下,生成的基元轨迹会强烈收敛到问题的最小规范解。当重标定正则化参数快速收敛为零时,系统在原始-双重间隙、违反可行性、目标残差和目标函数梯度法等方面沿轨迹都有较快的收敛速度,并且轨迹弱收敛于线性约束凸优化问题的原始-双重解。最后,进行了数值实验来说明理论结论。
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来源期刊
CiteScore
5.40
自引率
4.20%
发文量
437
审稿时长
3.0 months
期刊介绍: The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest. The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.
期刊最新文献
Editorial Board Fast convergence rates and trajectory convergence of a Tikhonov regularized inertial primal–dual dynamical system with time scaling and vanishing damping Developing and analyzing a FDTD method for simulation of metasurfaces An immersed interface neural network for elliptic interface problems A stochastic Bregman golden ratio algorithm for non-Lipschitz stochastic mixed variational inequalities with application to resource share problems
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