LPNN-based approach for LASSO problem via a sequence of regularized minimizations

In compressive sampling theory, the least absolute shrinkage and selection operator (LASSO) is a representative problem. Nevertheless, the non-differentiable constraint impedes the use of Lagrange programming neural networks (LPNNs). We present in this article the -LPNN model, a novel algorithm that tackles the LASSO minimization together with the underlying theory support. First, we design a sequence of smooth constrained optimization problems, by introducing a convenient differentiable approximation to the non-differentiable -norm constraint. Next, we prove that the optimal solutions of the regularized intermediate problems converge to the optimal sparse signal for the LASSO. Then, for every regularized problem from the sequence, the -LPNN dynamic model is derived, and the asymptotic stability of its equilibrium state is established as well. Finally, numerical simulations are carried out to compare the performance of the proposed -LPNN algorithm with both the LASSO-LPNN model and a standard digital method.     

一种自动布线方法：多级线探索法

本文介绍了一种在微机上实现的印制板自动布线方法──多级线探索法及其编程方法。这种方法是基于完备布线算法的概念，通过分析李氏算法和传统线探索法的不足之处而得到的。虽然它也是一种线探索法，但有较传统线探索法更强的探索能力，不需要结合李氏算法而能单独完成布线任务，是一种较理想的算法，通过实验获得了较为满意的效果。     

SPECTRAL DENSITY ESTIMATION FROM NONLINEARLY OBSERVED DATA

Abstract. The estimation of the spectral density function of a stationary Gaussian process at the input of an instantaneous nonlinearity is considered when the nonlinearity is known and a finite set of observations of the output process is given. A class of spectral estimates is considered and their quadratic-mean consistency is established; precise asymptotic expressions for their bias and covariance are derived and their asymptotic normality is obtained.     

Fixed point theorems on fuzzy normed linear spaces

In this paper, definitions of strongly fuzzy convergent sequence, l-fuzzy weakly convergent sequence and l-fuzzy weakly compact set are given in a fuzzy normed linear space. The concepts of fuzzy normal structure, fuzzy non-expansive mapping, uniformly convex fuzzy normed linear space are introduced and fixed point theorems for fuzzy non-expansive mappings are proved.     

THE ANALYSIS OF THE SEPARATED LAYERS ALGORITHM BY DOMAIN DECOMPOSITION METHOD

From the principle of of the Domain Decomposition Method (DDM), we analyse the 2nd-order linear elliptic partial differential problems and link the Separated-Layers Algorithm (SLA) with DDM. The mathematical properties of SLA and numerical example are presented to obtain satisfactory computation results. For general linear differential ones, also are the structure of SLA and its characteristics discussed.     

Expert system for dispatch control in restoration of ehv power system after complete blackout

Present-day power systems operate with high reliability, and it is rare that a blackout will extend over an entire system swiftly and securely. This paper considers automatic power supply to loads after a complete blackout of a system. First, taking into account characteristics of generators, loads, and initial power sources, a method is proposed of allocating several generators to each load in parallel to the system and supplying power to the load sequentially. Second, to remove the imbalance between supply and demand of power, a method is proposed of adjusting the amount of supply and generation according to a present imbalance and the sum of past ones. Third, to automatically issue orders for start-up, parallel, follow-up, stand-by, and stoppage of generators, several rules for each power station are set and an expert system is made based on them. Finally, the expert system is applied to a model power system, and it is verified that it can restore loads without any trouble for a complete blackout which occur at any time of a day and in any restoration pattern.     

A Survey on the Numerics and Computations for the Landau-Lifshitz Equation of Micromagnetism

The Landau-Lifshitz (LL)equation of micromagnetism governs rich variety of the evolution of magnetization patterns in ferromagnetic media. This is due to the complexity of physical quantities appearing in the LL equation. This complexity causes also an interesting mathematical properties of the LL equation: nonlocal character for some quantities,nonconvex side-constraints, strongly nonlinear terms. These effects influence also the numerical approximations. In this work, recent developments on the approximation of weak solutions, together with the overview of well-known methods for strong solutions,are addressed. Author is supported by the Fund for Scientific Research - Flanders FWO (Belgium).     

网络融合边界的电信DoS攻击检测*

为了检测网络融合边界的电信拒绝服务攻击,首先针对攻击的类型分别提出了基于呼叫统计或流量信号分析的检测方法,并采用分步骤的策略设计了检测系统,将两种检测算法分别应用于粗检测步骤,再通过精检测步骤确认攻击并找出攻击源.模拟实验结果表明,该方案能够有效地检测出典型的攻击,并能够实时在线检测,具有良好的实用价值,为应对网络融合所带来的新安全问题提供了一种解决方案.     

Dual–primal proximal point algorithms for extended convex programming

This paper presents a class of dual–primal proximal point algorithms (PPAs) for extended convex programming with linear constraints. By choosing appropriate proximal regularization matrices, the application of the general PPA to the equivalent variational inequality of the extended convex programming with linear constraints can result in easy proximal subproblems. In theory, the sequence generated by the general PPA may fail to converge since the proximal regularization matrix is asymmetric sometimes. So we construct descent directions derived from the solution obtained by the general PPA. Different step lengths and descent directions are chosen with the negligible additional computational load. The global convergence of the new algorithms is proved easily based on the fact that the sequences generated are Fejér monotone. Furthermore, we provide a simple proof for the O(1/t) convergence rate of these algorithms.     

广义双线性系统的终端滑模控制

研究广义双线性系统的终端滑模变结构控制问题.基于Lyapunov稳定性理论,运用Lyapunov函数方法,给出广义双系统的终端滑动模超出面,设计相应的终端滑模变结构控制器,使得闭环系统渐进稳定,实现滑动模运动,保证系统状态在有限时间内到达平衡点,得到广义双线性系统全局稳定的充分条件.所给的可行性算例,说明这一方法的有效性与可行性.