1) DC-Programming 直流写 1. The key killers to the retention of Flash memory are three different types of disturbances,DC-Programming, DC-Erasure, and Drain Disturbance. 直流写、直流擦以及漏极干扰是影响Flash存储器长期有效保存数据的主要原因,本文在Mohammad失效模型的基础上提出了一个更优的测试算法,...
We show that both problems can be cast as instances of DC-programming. We give an explicit decomposition of the corresponding functions as differences of convex functions (DC) and report the results of experiments demonstrating the effectiveness of the DCA algorithm applied to these problems.Pranjal...
DC. 3.Somesimpleexamples 1)x t Qx,Q=A-B,AandBarepositivesemi-definite. 2)x t y, 3)Letd M beadistancefunction,then d M (x)=inf{||x-y||:yinM}. Proofof3) 4.DCProgramming •4.1PrimalProblem •4.2DualProblem •4.3DCAlgorithm(DCA) 4.1PrimalProblem •Ageneralform 0 inf{():...
The year 2015 marks the 30th birthday of DC (Difference of Convex functions) programming and DCA (DC Algorithms) which constitute the backbone of nonconvex programming and global optimization. In this article we offer a short survey on thirty years of developments of these theoretical and algorithm...
Mathematical programming problems dealing with functions, each of which can be represented as a difference of two convex functions, are called DC programming problems. The purpose of this overview is to discuss main theoretical results, some applications, and solution methods for this interesting and ...
We propose some new DC (difference of convex functions) programming approaches for solving the Bilinear Matrix Inequality (BMI) Feasibility Problems and the Quadratic Matrix Inequality (QMI) Feasibility Problems. They are both important NP-hard problems in the field of robust control and system theory...
DC programming approaches for BMI and QMI feasibility problems. NIU Y S,TAO P D. Advanced Computational Methods for Knowledge Engineering . 2014Y. S. Niu and D. T. Pham, Dc programming approaches for bmi and qmi feasibility problems, Advanced Computational Methods for Knowledge Engineering: ...
DC programming, we prove that the proposed method is convergent to a critical point of the problem under some assumptions. Finally, we demonstrate numerically that our proposed algorithm performs better than the state-of-the-art DC algorithm and alternating direction method of multipliers (ADMM) ...
It relies on the family of nonconvex penalties which can be decomposed as a difference of convex functions (DC). This allows us to apply DC programming which is a generic and principled way for solving nonsmooth and nonconvex optimization problem. We also show that several algorithms in the ...
On the Linear Convergence of Difference-of-convex Algorithms for Nonsmooth DC Programming In this paper we consider the linear convergence of algorithms for minimizing differenceof-convex functions with convex constraints. We allow nonsmoothness in both of the convex and concave components in the object...