磁盘阵列错误隐藏的DCT系数重建算法研究

基于DCT变换的图象压缩，以块为单位进行DCT变换把图象从时域转换到领域，由于能量主要集中在少数低频系数，再结合量化、编码，可以实现有效的压缩，基于DCT的错误隐藏算法可用于客户端挖重建图象，隐藏存储系统或传输信道带来的错误，本文针对磁盘阵列中单个磁盘原失效，提出了三种客户端的基DCT编码的图象错误隐藏算法，并进行了验证。     

一种改进的时域优化捕获算法

针对信号在传输过程中存在时延、Doppler频移及多径衰落等,接收信号的中心频点以及PN码相位存在不确定性问题,通过时频域处理、分段及均值处理、移动序列处理、快速Doppler加权估计等手段,结合XFAST捕获算法、均值捕获算法和时域融合捕获算法的优点,提出一种改进的时域优化捕获算法,从复杂度、捕获时间、捕获精度的角度进行算法效能分析。Matlab仿真得出时域优化捕获算法的Doppler估计误差小,捕获比例峰值优于现有的其他两种算法,搜索速度明显提高。     

A frequency domain step response identification method for continuous-time processes with time delay

Step response test is widely practiced for model identification in process industry. A frequency domain step response identification method is proposed for obtaining a continuous-time process model with time delay. By introducing a damping factor to the step response for realization of Laplace transform, a frequency response estimation algorithm is first proposed, in which only single integral is needed for computation, compared to recently developed identification methods based on multiple integral in time domain. Based on the estimated frequency response, two model fitting algorithms are developed analytically for obtaining a time delay model of first-, second-, or higher order with repetitive poles. Another two algorithms based on fitting multiple frequency response points thus estimated are proposed for obtaining a time delay model of any order, the latter of which may also be used to improve fitting accuracy over a specified frequency range interested to control design. Meanwhile, practical strategies to consolidate identification robustness against measurement noise are given based on consistent estimation analysis, together with a guideline for model structure selection to realize optimal fitting for identification of a high order process. Illustrative examples from recent references are used to demonstrate the effectiveness and merits of the proposed identification algorithms.     

视频数据的错误隐藏算法研究

由于实时视频数据流在存储或传输中的错误、丢包等原因,解码器接收到的数据流可能不完整,无法正常解码。错误隐藏是解决这个问题的方法之一,文章回顾了当前的主要错误隐藏算法。根据视频编码的特点,对传输信道的错误隐藏算法进行了分类,包括时间、空间、时-空结合以及频域的相关算法,并对它们进行了比较和评述;同时对存储系统的错误隐藏算法也进行了分类比较和评述。最后对未来研究方向进行了展望,给出了若干值得研究的问题。     

Analysis of second-order sliding-mode algorithms in the frequency domain

A frequency domain analysis of the second-order sliding-mode algorithms, particularly of the twisting algorithm is carried out in the frequency domain with the use of the describing function method and Tsypkin's approach. It is shown that in the presence of an actuator, the transient process may converge to a periodic motion. Parameters of this periodic motion are analyzed. A comparison of the periodic solutions in the systems with higher order sliding-mode controllers and the oscillations that occur in classical sliding-mode systems with actuators is done.     

Physics-based modeling strategies for diagnostic and prognostic application in aerospace systems

This paper presents physics-based models as a key component of prognostic and diagnostic algorithms of health monitoring systems. While traditionally overlooked in condition-based maintenance strategies, these models potentially offer a robust alternative to experimental or other stochastic modeling data. Such a strategy is particularly useful in aerospace applications, presented in this paper in the context of a helicopter transmission model. A lumped parameter, finite element model of a widely used helicopter transmission is presented as well as methods of fault seeding and detection. Fault detection through diagnostic vibration parameters is illustrated through the simulation of a degraded rolling-element bearing supporting the transmission’s input shaft. Detection in the time domain and frequency domain is discussed. The simulation shows such modeling techniques to be useful tools in health monitoring analysis, particularly as sources of information for algorithms to compare with real-time or near real-time sensor data.     

Frequency‐dependent fault detection for networked systems under uniform quantization and try‐once‐discard protocol

This paper is concerned with the frequency‐dependent fault detection scheme for networked systems under uniform quantization and try‐once‐discard protocol scheduling. By considering the communication constraint and the data node scheduling, a switched system is firstly modeled to characterize the dynamic features of the whole system. The switching function of the derived system is determined by the try‐once‐discard protocol. For this class of system, a sufficient condition to ensure the exponentially ultimately boundedness is established. With the aid of some novel analysis processes, sufficient conditions to characterize the desired finite frequency performances, which transform the frequency‐domain restrictions into time‐domain conditions, are subsequently developed. Then, the fault detection filters corresponding to the transmission nodes are synthesized by solving an optimization problem. Finally, an application to VTOL aircraft is presented to illustrate the effectiveness of the proposed fault detection strategy.     

Pre-run-time scheduling to reduce schedule length in the FieldBusenvironment

The paper deals with the problem of scheduling the transmission of periodic processes in a distributed FieldBus system, defining the conditions guaranteeing correct transmission. The scheduling of periodic processes fixes the transmission times for each process in a table, whose length is equal to the Least Common Multiple (LCM) of all the periods. This involves great memorization problems when some periods are relatively prime. The authors identify the theoretical conditions which allow the length of the scheduling table to be drastically reduced, but still guarantee correct transmission. On the basis of the theoretical conditions given, the authors present a pre-run-time scheduling algorithm which determines a transmission sequence for each producing process within the desired scheduling interval. An online scheduling algorithm is also proposed to schedule new transmission requests which are made while the system is functioning. The reduction in the schedule length may increase the number of transmissions, thus reducing the effective bandwidth and increasing the communication overload. In order to make as complete an analysis as possible of the scheduling solution, the authors also present an analysis of both the computational complexity of the algorithms proposed and the communication overload introduced     

A neural network and multiple regression method for the characterization of the depth of weld penetration in laser welding based on acoustic signatures

The need for the control of the depth of weld penetration has been and remains of a long term interest in the automated welding process. In this study, the relationship between the depth of weld penetration and the acoustic signal acquired during the laser welding process of high strength steels is investigated. The acoustic signals are first preprocessed by the spectral subtraction noise reduction method and analyzed both in the time domain and frequency domain. Based on this analysis, two algorithms are developed to acquire the acoustic signatures. The acquired acoustic signatures are then used to characterize the depth of weld penetration by using a neural network and a multiple regression analysis. The results show that the acoustic signatures can characterize and predict the depth of weld penetration well under different laser welding parameters.     

Phase noise analysis of oscillators with Sylvester representation for periodic time-varying modulus matrix by regular perturbations

Phase noise analysis of an oscillator is implemented with its periodic time-varying small signal state equations by perturbing the autonomous large signal state equations of the oscillator. In this paper, the time domain steady solutions of os- cillators are perturbed with traditional regular method; the periodic time-varying Jocobian modulus matrices are decomposed with Sylvester theorem, and on the resulting space spanned by periodic vectors, the conditions under which the os- cillator holds periodic steady states with any perturbations are analyzed. In this paper, stochastic calculus is applied to disclose the generation process of phase noise and calculate the phase jitter of the oscillator by injecting a pseudo sinusoi- dal signal in frequency domain, representing the white noise, and a δ correlation signal in time domain into the oscillator. Applying the principle of frequency modulation, we learned how the power-law and the Lorentzian spectrums are formed. Their relations and the Lorentzian spectrums of harmonics are also worked out. Based on the periodic Jacobian modulus matrix, the simple algorithms for Floquet exponents and phase noise are constructed, as well as a simple case is demonstrated. The analysis difficulties and the future directions for the phase noise of oscillators are also pointed out at the end.     

Domain Decomposition Algorithms for Two Dimensional Linear Schrödinger Equation

This paper deals with two domain decomposition methods for two dimensional linear Schrödinger equation, the Schwarz waveform relaxation method and the domain decomposition in space method. After presenting the classical algorithms, we propose a new algorithm for the Schrödinger equation with constant potential and a preconditioned algorithm for the general Schrödinger equation. These algorithms are then studied numerically. The numerical experiments show that the new algorithms can improve the convergence rate and reduce the computation time. Besides of the traditional Robin transmission condition, we also propose to use a newly constructed absorbing condition as the transmission condition.     

A note on causal and CITE iterative learning control algorithms

The convergence properties of causal and current iteration tracking error (CITE) discrete time iterative learning control (ILC) algorithms are studied using time and frequency domain convergence criteria. Of particular interest are conditions for monotone convergence, and these are evaluated using a discrete-time version of Bode's integral theorem.     

Diffusion approximation of frequency sensitive competitive learning

The focus of this paper is a convergence study of the frequency sensitive competitive learning (FSCL) algorithm. We approximate the final phase of FSCL learning by a diffusion process described by the Fokker-Plank equation. Sufficient and necessary conditions are presented for the convergence of the diffusion process to a local equilibrium. The analysis parallels that by Ritter-Schulten (1988) for Kohonen's self-organizing map. We show that the convergence conditions involve only the learning rate and that they are the same as the conditions for weak convergence described previously. Our analysis thus broadens the class of algorithms that have been shown to have these types of convergence characteristics.     

Identification and frequency domain analysis of non-stationary and nonlinear systems using time-varying NARMAX models

This paper introduces a new approach for nonlinear and non-stationary (time-varying) system identification based on time-varying nonlinear autoregressive moving average with exogenous variable (TV-NARMAX) models. The challenging model structure selection and parameter tracking problems are solved by combining a multiwavelet basis function expansion of the time-varying parameters with an orthogonal least squares algorithm. Numerical examples demonstrate that the proposed approach can track rapid time-varying effects in nonlinear systems more accurately than the standard recursive algorithms. Based on the identified time domain model, a new frequency domain analysis approach is introduced based on a time-varying generalised frequency response function (TV-GFRF) concept, which enables the analysis of nonlinear, non-stationary systems in the frequency domain. Features in the TV-GFRFs which depend on the TV-NARMAX model structure and time-varying parameters are investigated. It is shown that the high-dimensional frequency features can be visualised in a low-dimensional time–frequency space.     

基于频域和空域的数字图像复原算法研究

基于频域和基于空域的数字图像复原算法有各自的适用范围和特点.通过分析研究可以得到,基于频域的算法比较简单,在已知图像和噪声功率谱的情况下可以快速准确地进行图像复原;基于空域的算法直接对图像像素进行操作,通过正则化项的引入更好地控制噪声,并采用迭代计算获得了良好的图像复原效果.文中对常规的空域正则化算法进行改进,构造空域上加权矩阵,更好地保持图像的边缘和纹理.在实际应用中要需要对这些不同算法加以比较选择.     

基于路谱频域的车身疲劳分析

针对车身疲劳分析中静载法无法考虑结构动力学响应,瞬态分析法无法求解过长时间域的问题,将这2种方法与频域法进行比较,发现用频域法对大规模有限元模型进行动态疲劳分析相对容易,并能完全描述动力学响应过程.根据频域法进行振动疲劳分析的理论和计算过程,给出基于路谱频域的车身疲劳分析流程.基于功率谱密度（Power Spectral Density,PSD）载荷谱的传递函数法求解某车关键部件的疲劳寿命,求解结果与疲劳试验结果比较一致.结果表明基于路谱频域的振动疲劳分析方法在汽车结构疲劳计算中的应用可行.     

单幅光学遥感影像去霾算法及评价综述

光学遥感影像经常受到云或霾影响,而在多数情况下极少能获取辅助数据用于遥感影像去霾;因此单幅光学遥感影像的图像处理去霾算法成为遥感影像预处理的重要技术。目前,不同研究者设计了多种算法,但是缺乏系统性的总结与对比分析,本文旨在系统性地总结单幅遥感影像去霾算法的研究进展,并提供典型算法的基本原理、优缺点及适用场景。采用文献综合分析方法从霾条件影像成像模型、基础原理和结果评价3方面对当前的去霾算法进行归类总结和原理剖析,然后结合具体应用场景分析算法的适用范围和存在问题,并提出可行的解决方案。常见的去霾算法大体可归纳为暗目标减法、滤波法、暗通道先验法和经验变换法4类,这些算法采用的霾条件影像成像模型包括加法模型、霾传输衰减模型和照明—反射模型等;在算法的评估中,常用的手段有主观分析方法、影像光谱特征分析方法以及图像质量指标评估法等。现有算法并不能适用于所有的场景或图像,存在模型参数难以自适应调整、模型对特殊地物类型敏感、处理结果失真严重等问题;算法的评价主要采用主观对比分析方法,根据应用需求构建客观指标成为目前的热点方向。     

Improving listeners' experience for movie playback through enhancing dialogue clarity in soundtracks

This paper presents a method for improving users' quality of experience through processing of movie soundtracks. The dialogue clarity enhancement algorithms were introduced for detecting dialogue in movie soundtrack mixes and then for amplifying the dialogue components. The front channel signals (left, right, center) are analyzed in the frequency domain. The selected partials in the center channel signal, which yield high disparity between left and right channels, are detected as dialogue. Subsequently, the dialogue frequency components are boosted to achieve an increased dialogue intelligibility. Techniques for reduction of artifacts in the processed signal are also introduced. It is done through smoothing in the time domain and in the frequency domain, applied to reduce unpleasant artifacts. The results of objective and subjective tests are provided, which prove that an increased dialogue intelligibility is achieved with the aid of the proposed algorithm. The algorithm is particularly applicable in mobile devices while listening in changing conditions and in the presence of noise.     

Nonlinear Dynamics in the Motion of Floating Cranes

The nonlinear dynamics of a floating crane is investigated. The motion of the system – consisting of the hull with the crane, the load and a nonlinear mooring system – was found to exhibit various nonlinear phenomena. Operating conditions, in which the motion of the vessel or the load is highly dependent on the initial conditions or disturbances are of special interest. Bifurcations in which a small change of a parameter value causes a large qualitative change of the dynamics often limit the range of save operation.For a floating crane which is periodically forced by waves, different mathematical tools are used to investigate resonances and subharmonic motions. The multiple-scales method allows for the analysis in frequency domain and path following algorithms are applied for a numerical bifurcation analysis. The results of both methods agree very well with each other and both offer tools that could help for the evaluation of operating conditions of crane vessels.     

一种改进的MIMO-OFDM系统频域信道估计和跟踪方案

深入研究了MIMO-OFDM系统中的频域信道估计和跟踪算法．在分析比较了现有频域信道估计算法的基础上,提出了一种有效的改进频域信道估计和跟踪方案．该方案利用基于正交训练符号的算法求得初始信道估计值,利用信道估计和信号检测的联合迭代算法来跟踪随时间变化的信道参数．在典型的室内传输环境下对三种频域信道估计和跟踪方案进行了仿真比较,结果表明,本文所提方案在较低的迭代次数下就可以带来明显的性能改善．