Iterative Regularization and Nonlinear Inverse Scale Space in Curvelet-type Decomposition Spaces

In this paper we generalize the iterative regularization method and the inverse scale space method, recently developed for wavelet-based image restoration, to curvelet-type decomposition spaces setting. We obtain the result that minimzer of the new model can be derived as curvelet firm shrinkage with curvelet-type weight, which is dynamically changing in the iteration（CDS-IRM）. And we obtain a new class of nonlinear inverse scale spaces flow which is dependent on Curvelet-type decomposition scale and smooth order（CDS-ISS）. Numerical experiments indi- cate that the proposed methods are very eflClcient for de- noising.     

基于图正则化与非负组稀疏的自动图像标注

设计一个稳健的自动图像标注系统的重要环节是提取能够有效描述图像语义的视觉特征。由于颜色、纹理和形状等异构视觉特征在表示特定图像语义时所起作用的重要程度不同且同一类特征之间具有一定的相关性,该文提出了一种图正则化约束下的非负组稀疏(Graph Regularized Non-negative Group Sparsity, GRNGS)模型来实现图像标注,并通过一种非负矩阵分解方法来计算其模型参数。该模型结合了图正则化与l2,1-范数约束,使得标注过程中所选的组群特征能体现一定的视觉相似性和语义相关性。在Corel5K和ESP Game等图像数据集上的实验结果表明：相较于一些最新的图像标注模型,GRNGS模型的鲁棒性更强,标注结果更精确。     

Automatic Decomposition of the Clinical Electromyogram

We describe a new, automatic signal-processing method (ADEMG) for extracting motor-unit action potentials (MUAP's) from the electromyographic interference pattern for clinical diagnostic purposes. The method employs digital filtering to select the spike components of the MUAP's from the background activity, identifies the spikes by template matching, averages the MUAP waveforms from the raw signal using the identified spikes as triggers, and measures their amplitudes, durations, rise rates, numbers of phases, and firing rates. Efficient new algorithms are used to align and compare spikes and to eliminate interference from the MUAP averages. In a typical 10-s signal recorded from the biceps brachii muscle using a needle electrode during a 20 percent-maximal isometric contraction, the method identifies 8-15 simultaneously active MUAP's and detects 30-70 percent of their occurrences. The analysis time is 90 s on a PDP-11/34A.     

利用终点吸引子与正则化神经网络求解最小向量范数问题

本文结合终点吸引子与罚函数方法,构造了求解满足约束条件的最小向量范数问题的终点吸引子神经网络模型,所提出的方法克服了惩罚因子须取充分大的要求,使得网络易于收敛于稳定状态。利用正则化方法解决了求解向量范数极小化中的病态问题,从而得到了一个正则化神经网络。所有的网络均给出了电路结构图,我们的方法有利于ＶＬＳＩ实现及其实时求解。用具体例子进行了模拟实验,实验结果说明了方法的正确性与有效性。     

Analysis and Regularization of the TD-EFIE Low-Frequency Breakdown

Low-frequency breakdown phenomenon plaguing marching-on-in-time solutions of time domain electric field integral equations is analyzed and cured. A theoretical analysis of the breakdown identifies deficiencies in the treatments proposed to date. A scheme for eliminating low frequency breakdown phenomena that leverages hierarchical regularization is presented. It applies to arbitrary meshes and gives rise to linear systems that are better conditioned than those obtained with standard loop-star/tree bases. The scheme's analytical properties and numerical results demonstrate its efficacy in accelerating the iterative solution of the time domain electric field integral equations.      

Exact Dynamics of Automatic Gain Control

The exact input-output relationship is derived for a firstorder automatic gain control loop wherein the variable gain is an exponential function of the gain control voltage. The exact solution is compared to the linearized solution, and the condition for valid linearization is given.     

Communication Over MIMO X Channels: Interference Alignment, Decomposition, and Performance Analysis

In a multiple-antenna system with two transmitters and two receivers, a scenario of data communication, known as the X channel, is studied in which each receiver receives data from both transmitters. In this scenario, it is assumed that each transmitter is unaware of the other transmitter's data (noncooperative scenario). This system can be considered as a combination of two broadcast channels (from the transmitters' points of view) and two multiple-access channels (from the receivers' points of view). Taking advantage of both perspectives, two signaling schemes for such a scenario are developed. In these schemes, some linear filters are employed at the transmitters and at the receivers which decompose the system into either two noninterfering multiple-antenna broadcast subchannels or two noninterfering multiple-antenna multiple-access subchannels. The main objective in the design of the filters is to exploit the structure of the channel matrices to achieve the highest multiplexing gain (MG). It is shown that the proposed noncooperative signaling schemes outperform other known noncooperative schemes in terms of the achievable MG. In particular, it is shown that in some specific cases, the achieved MG is the same as the MG of the system if full cooperation is provided either between the transmitters or between the receivers. In the second part of the paper, it is shown that by using mixed design schemes, rather than decomposition schemes, and taking the statistical properties of the interference terms into account, the power offset of the system can be improved. The power offset represents the horizontal shift in the curve of the sum-rate versus the total power in decibels.     

Shared Content Management in Replicated Web Systems: A Design Framework Using Problem Decomposition, Controlled Simulation, and Feedback Learning

Replication is one of the primary techniques used to improve the quality of distributed content service. It generally reduces user latencies and increases a site's availability. However, to our knowledge, there is no systematic framework that combines the structure of both content and service components of a Web application to design effective replica hosting architectures. Recent advances in interconnected and multiple content distribution network (CDN) architectures render this problem even more complex. In this study, we develop a systematic framework for designing and evaluating large-scale, component-based replication architectures for Web systems that are driven by both the quality and effectiveness of service provisioning on the service network. The proposed framework employs a combination of problem decomposition, configuration evaluation through controlled system simulations, and a neural-network-based feedback learning mechanism in the exploration of the design space. A case study demonstrates the viability of the framework. The framework can be an effective decision support tool for a system designer to systematically explore design options and select an appropriate design configuration that best meets the desired design objectives.     

Implementations of Sorted-QR Decomposition for MIMO Receivers: Complexity,Reusability and Efficiency Analysis

Matrix decomposition of the channel matrix in the form of QR decomposition (QRD) is needed for advanced multiple input and multiple output (MIMO) demapping algorithms like sphere decoder. Due to the computation-intensive nature of the QRD, its implementation has to be highly efficient. Flexibility in several forms, e.g. support for different algorithms, reusability of wireless implementations, portability, etc. is highly sought in wireless devices. The contradictory nature of flexibility and efficiency requires tradeoffs to be made between them in system development. In this paper, we have analyzed such tradeoffs by implementing two minimum mean squared error-sorted QRD algorithms. The algorithms have been implemented in four different methods with varying degree of reusability and in five different forms of portability. The performance of the implementations is evaluated by using the real-time constraints from the LTE standard. For all the implementations, modular equations for accurately estimating the execution time are derived.     

Analysis and Regularization of the Thin-Wire Integral Equation With Reduced Kernel

For the straight wire, modeled as a hollow tube, we establish a conditional equivalence relation between the integral equations with exact and reduced kernel. This relation allows us to examine the existence and uniqueness conditions for the integral equation with reduced kernel, based on a local argument. Further, we characterize the ill-posedness of integral equation with reduced kernel and we propose a regularization and filtering procedure to extend the range of this integral equation     

特征空间分解算法分析与仿真

卫星导航信号为扩频信号,比接收机热噪声低20~30dB,极易受到干扰,因此,研究卫星导航系统接收机的抗干扰能力显得极为重要。特征空间算法是一种有效的自适应抗干扰算法,目前广泛应用于抗干扰接收机中。首先建立了阵列信号基本模型,然后介绍了阵列信号特征分解原理,对其性能进行分析,并由计算机仿真证明了该算法的有效性。     

一种快速计算多柱体散射问题的区域分解时域有限差分方法

本文提出一种用于计算多柱体散射问题的区域分解时域有限差分算法（DD-FDTD）。当各散射柱体相互间距离比较远时,采用经典的FDTD方法进行计算时,计算域是非常大的,大量的网络浪费在射体之间。文中我们使用区域分解的思想,把各个柱体处理为各个子域。各柱体间大量的网格被省去,代之以二维时域Green函数将各个子域连接起来。采用近远场变换方法,并将柱体间互偶处理为等效柱面波入射场,从而大大压缩了计算时间。由于二维时域Green函数含有关于时间的积分,且此积分是一个反常积分,采用半解析的方法,精确地算出了其中的反常积分值,大幅度提高了计算精度。最终,使该方法得以实现。     

Unleashing the Effectiveness of Process-Oriented Information Systems: Problem Analysis, Critical Success Factors, and Implications

Process-oriented information systems (IS) aim at the computerized support of business processes. So far, contemporary IS have often fail to meet this goal. To better understand this drawback, to systematically identify its rationales, and to derive critical success factors for business process support, we conducted three empirical studies: an exploratory case study in the automotive domain, an online survey among 79 information technology professionals, and another online survey among 70 business process management experts. This paper summarizes the findings of these studies, puts them in relation with each other, and uses them to show that ";process orientation"; is scarce and ";process awareness"; is needed in IS engineering.     

基于lk范数的SAR复图像域正则化方法分析及改进

正则化方法通过增加先验信息约束实现合成孔径雷达(SAR)图像的超分辨和噪声抑制,为目标识别提供了更高质量的图像信息。该文通过对基于lk范数的SAR复图像域正则化方法迭代过程的分析,揭示其增强分辨率的内在机理,并针对原有方法在不同强度散射点条件下分辨率提高不一致的问题,提出采用可变的正则化参数对其进行改进。仿真数据和MSTAR实测数据的实验结果证实了改进方法的有效性。     

Decomposition and Analysis of Process Variability Using Constrained Principal Component Analysis

Process-induced variability has become a predominant limiter of performance and yield of IC products especially in a deep submicron technology. However, it is difficult to accurately model systematic process variability due to the complicated and interrelated nature of physical mechanisms of variation. In this paper, a simple and practical method is presented to decompose process variability using statistics of the measurements from manufacturing inline test structures without assuming any underlying model for process variation. The decomposition method utilizes a variant of principal component analysis and is able to reveal systematic variation signatures existing on a die-to-die and wafer-to-wafer scale individually. Experimental results show that the most dominant die-to-die variation and wafer-to-wafer variation represent 31% and 25% of the total variance of a large set of manufacturing inline parameters in 65-nm SOI CMOS technology. The process variation in RF circuit performance is also analyzed and shown to contain 66% of process variation obtained with manufacturing inline parameters.     

“背包问题”算法设计及分析

“背包问题”是一个典型问题．其求解也是算法设计及验证的一个热点。在此分别采用优先策略、动态规划及递归三种不同方法对“背包问题”进行求解、算法设计及验证。实践证明了三种算法的正确性。在复杂度分析中．优先策略算法的空间及时间复杂度最低,而动态规划法具有明显的优势。     

Decomposition in Reliability Analysis of Fault-Tolerant Systems

Two important problems which arise in modeling fault-tolerant systems with ultra-high reliability requirements are discussed. 1) Any analytic model of such a system has a large number of states, making the solution computationally intractable. This leads to the need for decomposition techniques. 2) The common assumption of exponential holding times in the states is intolerable while modeling such systems. Approaches to solving this problem are reviewed. A major notion described in the attempt to deal with reliability models with a large number of states is that of behavioral decomposition followed by aggregation. Models of the fault-handling processes are either semi-Markov or simulative in nature, thus removing the usual restrictions of exponential holding times within the coverage model. The aggregate fault-occurrence model is a non-homogeneous Markov chain, thus allowing the times to failure to possess Weibull-like distributions. There are several potential sources of error in this approach to reliability modeling. The decomposition/aggregation process involves the error in estimating the transition parameters. The numerical integration involves discretization and round-off errors. Analysis of these errors and questions of sensitivity of the output (R(t)) to the inputs (failure rates and recovery model parameters) and to the initial system state acquire extreme importance when dealing with ultra-high reliability requirements.     

Analysis and Automatic Classification of Breath Sounds

Analysis of breath sounds (auscultation) is an important part of the diagnosis of pulmonary diseases. An automatic breathsounds classification scheme is suggested. Types of normal and abnormal breath sounds are classified, with the goal of providing the physician with a diagnostic assist device. The classification is performed in two levels. The first level is based on the linear prediction coefflcients, and the second level on energy envelope features. Seven types of breath sounds were classified. Out of 105 trials, the system exhibited only five errors The system can be implemented on a microprocessor and thus can be offered as a low-cost clinical instrument.