压缩感知及其图像处理应用研究进展与展望

压缩感知理论（Compressed sensing,CS）通过少量的线性测量值感知信号的原始结构,并通过求解最优化问题精确地重构原信号.该理论减少了数字图像及视频 获取时的存储及传输代价,也为后续的图像处理及识别的研究提供了新的契机,促进了理论和工程应用的结合. 阐述了CS的基本原理,综述了其关键技术稀疏变换、观测矩阵 设计、重构算法的一系列最新理论成果和发展,深入分析和比较了CS理论应用到图像处理领域的研究和发展状况,总结了其中存在的问题,并对未来的应用前景进行了展望.     

自适应天线匹配低频RFID读写器设计

在工业现场、野外甚至水中,RFID读写器天线电特性参数将发生改变,导致阻抗不匹配和发射功率大幅下降,最终降低RFID读写器读写范围和效率。为了解决这个问题,构建了一个自适应天线匹配RFID读写器系统,该系统在基本读写器系统上增加了自适应电容匹配矩阵、正弦波均方根检测和模/数转换器。该系统通过依次配置电容矩阵,扫描天线发射信号幅度,检测出最佳匹配电容,实现天线阻抗的最佳匹配。通过实验表明,在一定范围内该系统能够实现自动的阻抗匹配,获取最大发射功率。     

Investigation on the properties of a three‐component copolymer consisting of tris(allylphenoxy) triazine monomer and a diamine‐chain‐extension bismaleimide

A new type of modified bismaleimide resin was obtained by copolymerization between tris(allylphenoxy)triazine monomer (TAPT) and an aromatic diamine‐chain‐extension bismaleimide [e.g., 4,4′‐diaminodiphenylmethane (DADPM)‐chain‐extension 4,4′‐bismaleimidodiphenylmethane (BMDPM)]. The new three‐component‐polymer system had good processibility and mechanical properties. Better results were obtained when the weight ratio of TAPT to the DADPM‐chain‐extension BMDPM resin was 30%. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 93: 475–480, 2004     

H∞ filtering for discrete-time systems subject to stochastic missing measurements: a decomposition approach

This paper deals with the problem of H_∞ filtering for discrete-time systems with stochastic missing measurements. A new missing measurement model is developed by decomposing the interval of the missing rate into several segments. The probability of the missing rate in each subsegment is governed by its corresponding random variables. We aim to design a linear full-order filter such that the estimation error converges to zero exponentially in the mean square with a less conservatism while the disturbance rejection attenuation is constrained to a given level by means of an H_∞ performance index. Based on Lyapunov theory, the reliable filter parameters are characterised in terms of the feasibility of a set of linear matrix inequalities. Finally, a numerical example is provided to demonstrate the effectiveness and applicability of the proposed design approach.     

State estimation for complex systems with randomly occurring nonlinearities and randomly missing measurements

This paper is concerned with the state estimation problem for the complex networked systems with randomly occurring nonlinearities and randomly missing measurements. The nonlinearities are included to describe the phenomena of nonlinear disturbances which exist in the network and may occur in a probabilistic way. Considering the fact that probabilistic data missing may occur in the process of information transmission, we introduce the randomly data missing into the sensor measurements. The aim of this paper is to design a state estimator to estimate the true states of the considered complex network through the available output measurements. By using a Lyapunov functional and some stochastic analysis techniques, sufficient criteria are obtained in the form of linear matrix inequalities under which the estimation error dynamics is globally asymptotically stable in the mean square. Furthermore, the state estimator gain is also obtained. Finally, a numerical example is employed to illustrate the effectiveness of the proposed state estimation conditions.     

Sliding mode control for Markov jump linear uncertain systems with partly unknown transition rates

In this paper, based on sliding mode control approach, the robust stabilisation problem for a class of continuous-time Markovian jump linear uncertain systems with partly unknown transition rates is investigated. The transition rate matrix under consideration covers completely known, boundary known and completely unknown elements. By making use of linear matrix inequalities technique, sufficient conditions are presented to derive the linear switching surface and guarantee the stochastic stability of sliding mode dynamics. Then a sliding mode control law is designed to drive the state trajectory of the closed-loop system to the specified linear switching surface in finite time in spite of the existing uncertainties and unknown transition rates. Finally, an example is given to verify the validity of the theoretical results.     

Stability analysis and controller synthesis for discrete uncertain singular fuzzy systems with distinct difference matrices in the rules

This paper mainly studies an extended discrete singular fuzzy model incorporating the multiple difference matrices in the rules and discusses its stability and design issues. By embracing additional algebraic constraint, traditional discrete Takagi-Sugeno (T-S) fuzzy model can be extended to a generalised discrete singular Takagi-Sugeno (GDST-S) model with individual difference matrices E_i in the locally singular models, where it can describe a larger class of physical or non-linear systems. Based on the linear matrix inequality (LMI) approach, we focus on deriving some explicit stability and design criteria expressed by the LMIs for the regarded system. Thus, the stability verification and controller synthesis can be performed by the current LMI tools. Finally, some illustrative examples are given to illustrate the effectiveness and validity of the proposed approach.     

多次顶空固相微萃取方法的原理及应用

详细讨论了多次顶空固相微萃取(MHS-SPME)技术的原理和影响因素,并与常用的固相微萃取(SPME)定量校正方法相比较,分析了该方法的优势和缺点。综述了多次顶空固相微萃取在食品、农业领域的应用情况,并对该方法存在的问题和发展前景进行了论述。     

Isolation of Whole-plant Multiple Oscillations via Non-negative Spectral Decompositio

Constrained spectral non-negative matrix factorization（NMF）analysis of perturbed oscillatory process control loop variable data is performed for the isolation of multiple plant-wide oscillatory sources.The technique is described and demonstrated by analyzing data from both simulated and real plant data of a chemical process plant. Results show that the proposed approach can map multiple oscillatory sources onto the most appropriate control loops,and has superior performance in terms of reconstruction accuracy and intuitive understanding compared with spectral independent component analysis（ICA）.