Adaptive threshold to guarantee both detection and false alarm probabilities in multi-taper based spectrum sensing

The multi-taper spectrum (MTS) estimator enjoys a relatively low computational complexity and high estimation accuracy making it an attractive method for spectrum sensing in cognitive radio (CR) networks. However, it is difficult to guarantee both detection and false alarm probabilities when its design is based on fixed threshold, especially when the noise power fluctuates due to channel conditions. In this paper, a new adaptive threshold method to guarantee both detection and false alarm probabilities for MTS based spectrum sensing is proposed. By means of estimating noise power and signal power, the decision of adaptive threshold is able to adapt the noise fluctuation and achieve efficient trade-off between detection and false alarm probabilities. A closed form expression for the adaptive threshold is derived for both additive white Gaussian noise (AWGN) channel and multipath fading channel. Several metrics are employed to compare the performance of the proposed adaptive threshold method with that of the fixed threshold methods such as: error decision probability, detection probability, false alarm probability and throughput. The obtained results show that the proposed method achieves better spectrum efficiency and high throughput in comparison with the conventional fixed and adaptive threshold methods presented in the literature.     

一种基于独立联合K-分布CFAR的舰船检测算法

分析了中高分辨率SAR海洋图像的目标和海杂波特点. 利用舰船目标的灰度相关性和形状特性与背景杂波的差异,提出了一种基于独立联合K-分布CFAR的舰船检测算法. 算法建立了海杂波的二维独立联合K-分布概率模型,通过给定的虚警率得到检测阈值以对图像进行检测. 该算法能够极大地抑制斑点噪声和背景局部不均匀对检测带来的影响,有效地降低了虚警数,检测效果得到了明显改善.     

N-step off-line MPC design of nonhomogeneous Markov jump systems: A suboptimal case

This paper mainly concerns N-step off-line suboptimal predictive controller design for discrete nonhomogeneous Markov jump systems, in which the Markov chains are time-varying transition probabilities matrix modeled as a polytope. The design procedure is divided into N-step, more precisely, the first is to design the Nth step when the changes of Euclidean form of mode-dependent feedback law between the Nth and the (N+1)th asymptotically stable mode-dependent ellipsoids are less than the given accuracy. Then the N  th asymptotically stable mode-dependent invariant ellipsoid is defined. In the previous (N−1)$(N-1)$ steps, an off-line mode-dependent predictive controller is designed to drive the state to this small area including the origin. Compared with on-line MPC algorithm, the computation time is dramatically reduced while the dynamic performance of controller is comparable. One numerical example is presented to illustrate the validity of the developed results.     

一种改进的基于马尔科夫链的扩频图像隐写分析方法

提出一种对基于扩频信息隐藏图像进行隐写分析的方法.应用马尔科夫链模型,根据图像的相邻像素点之间的相关性,结合阈值判别方法和改进的模式识别方法,判断一幅图像中是否存在隐写信息.在Corel图像库上的实验表明,本方法降低了虚警率,且正检率的性能优于已有方法.     

Robust stabilization of non-stationary Markov jump 2-D systems with multiplicative noises

This paper deals with the problem of stabilization via synchronous state-feedback control for two-dimensional (2-D) discrete-time Roesser systems with stochastic parameters involving switchings and multiplicative stochastic noises. The switching process is driven by an inhomogeneous Markov chain whose transition probability matrix is piecewise time-invariant and external disturbances are of the type of white noises, which get multiplied into both system state and input vectors. Stability and tractable controller design conditions are derived based on a 2-D mode-dependent Lyapunov function approach, which are validated by a numerical example with simulations.     

Probability-guaranteed secure consensus control for time-varying stochastic multi-agent systems under mixed attacks

In this paper, the secure consensus control issue is investigated for a class of discrete time-varying stochastic multi-agent systems (MASs) subject to cyber-attacks. In order to give a comprehensive characterization of malicious threats against communication networks, a generic model is presented to take into account both random false data injection attacks (FDIAs) and replay attacks. The main objective of the problem under study is to design a control protocol via output feedback such that, despite the existence of mixed attacks, all the individual agents can be driven to reside within a desired ellipsoidal region in a pre-specified probability. Sufficient conditions are provided for the existence of the requested controller and the feedback gains are formulated in terms of the solution to certain matrix inequalities. Within the established framework, two optimization problems are considered with the aim to ensure the sub-optimal consensus performances from different perspectives. Finally, a simulation example is employed to illustrate the validity of the proposed control scheme.     

An event-triggered asynchronous H∞ filtering for singular Markov jump systems with redundant channels

In this paper, the problem of asynchronous H_∞ filtering for singular Markov jump systems with redundant channels under the event-triggered scheme is studied. In order to save the resource of bandwidth limited network and improve quality of data transmission, we utilize event-triggered scheme and employ redundant channels. The redundant channels are modeled as two mutually independent Bernoulli distributed random variables. To formulate the asynchronization phenomena between the system modes and the filter modes, the hidden Markov model is proposed so that the filtering error system has become a singular hidden Markov jump system. The criterion of regular, causal and stochastically stable with a certain H_∞ performance for the filtering error system has been obtained. The co-design of asynchronous filter and the event-triggered scheme is proposed in terms of a group of feasible linear matrix inequalities. Two examples are given to show the effectiveness of the proposed method.     

Observer-based control for singular nonhomogeneous Markov jump systems with packet losses

This paper is concerned with the observer-based H_∞ control for a class of singular Markov jump systems over a finite-time interval, where the transition probability (TP) is time-varying and is limited to a convex hull. Due to the limited capacity of network medium, packet losses are presented in the underlying systems. Firstly, using a stochastic Lyapunov functional, a sufficient condition on singular stochastic H_∞ finite-time boundedness for the corresponding closed-loop error systems is provided. Subsequently, a linear matrix inequality (LMI) condition on the existence of the H_∞ observer-based controller is developed from a new perspective. Finally, three numerical examples are provided to illustrate the effectiveness of the proposed controller design method, wherein it is shown that the proposed method yields less conservative results than those in the literature.     

Robust mixed H2/H∞ model predictive control for Markov jump systems with partially uncertain transition probabilities

This paper addresses the control problem for a class of discrete-time Markov jump linear systems with partially unknown transition probabilities using model predictive controller subject to external disturbances and input constraints. Our focus is on the design of a model predictive controller to stabilize the system with a given mixed H₂/H_∞ performance index. Sufficient conditions are derived in terms of a set of linear matrix inequalities. Examples are presented to demonstrate the effectiveness of the proposed controller design method.     

Reliable H∞ control on saturated linear Markov jump system with uncertain transition rates and asynchronous jumped actuator failure

This paper is concerned with reliable H_∞?control for saturated linear Markov jump systems with uncertain transition rates and asynchronous jumped actuator failure. The actuator failures are assumed to occur randomly under the Markov process with a different jumping mode from the system jumping mode. In considering the mixed-mode-dependent state feedback controller, both H_∞ stochastic stability analysis for closed-loop system with completely accessible transition rates and uncertain transition rates are investigated. Moreover, based on the obtained stability conditions, the H_∞?control problems are investigated, and the controller gains can be obtained by solving a convex optimization problem with minimizing H_∞ performance as objective and linear matrix inequalities (LMIs) as constraints. The problem of designing state feedback controllers such that the estimate of the domain of attraction is enlarged is also formulated and solved as an optimization problem with LMI constraints. Simulation results are presented to illustrate the effectiveness of the proposed results.     

Variational Bayesian based adaptive PDA filter in scenarios with unknown detection probability and heavy-tailed process noise

For target tracking systems, the probability of detecting a target is difficult to determine, and the process noise often has non-Gaussian heavy-tailed characteristics owing to interference from outliers. To address the issues associated with single target tracking within clutters in scenarios with an unknown detection probability and heavy-tailed process noise, this paper presents a variational Bayesian-based adaptive probabilistic data association filter (VB-APDAF). The beta distribution, Pearson type VII distribution and multinomial distribution are used to model the detection probability, the process noise, and the association events, respectively. To guarantee the conjugation, a novel parameter estimation strategy is employed. In this strategy, the previous state is introduced in the state update process to construct the joint probability density function of parameters to be estimated and data set. The VB framework is used to estimate the target state, detection probability, and associated events. An experiment was performed under simulated conditions to demonstrate the effectiveness of the proposed filter.     

Learning control for linear systems under general data dropouts at both measurement and actuator sides: A Markov chain approach

This paper contributes to the convergence analysis of iterative learning control for linear systems under general data dropouts at both measurement and actuator sides. By using a simple compensation mechanism for the dropped data, the sample path behavior along the iteration axis is analyzed and formulated as a Markov chain first. Based on the Markov chain, the recursion of the input error is reformulated as a switching system, and then a novel convergence proof is established in the almost sure sense under mild design conditions. Illustrative examples are provided to verify the theoretical results.     

基于马尔可夫链的专利产业化概率模型:专利引证的视角

从专利引证的视角,运用数理统计的方法衡量专利在技术发展过程中的重要性和价值,从定量分析入手对专利产业化的概率进行辨析。论证了专利产业化的判别与评价原理。专利引证网络的时间无关性、不可约性以及引证路径单向性满足马尔可夫链收敛的条件。运用马尔可夫链对专利引证网络的随机浏览过程进行建模。建立了专利引证网络与马尔可夫链的对应关系,将专利产业化概率的计算过程转化为计算马尔可夫链转移矩阵稳态分布的过程,设计了转移矩阵最大特征值和特征向量的迭代算法。从美国专利商标局的专利数据库中采集了235项1976年至2006年授权的半导体制造领域电子发射器制造技术的相关专利,分析了专利的年度分布情况。从美国国家经济研究局的专利数据集中查询得到592条专利引证关系,利用网络分析软件Pajek构建专利引证网络。实验结果表明,本文提出专利产业化概率模型切实有效,与专利产业化的实际情况相符,可以作为专利产业化可能性的一种指示。     

A stochastic process generated by a network with a randomly alternating switch

We consider in this paper a stochastic process which is generated in a network which is composed of a source, two loads and a switch which alternates randomly between the two loads. We compute the probability density, the joint probability density, the average and autocorrelation of the generated process. The results of this paper may have applications to electric power systems.     

一种分布式防盗报警系统的设计

本文提出了一种基于单片机信号处理的分布式防盗报警系统的软硬件设计方法,该系统包含有线式探测头和无线式探测头,探测头可以是基于热释电的主动式红外传感器或者是基于多普勒频移原理的微波雷达传感器。该系统具有检测范围大、组网方便灵活、灵敏度可调等优点,通过对软件算法的优化,使得系统具有较高的可靠性,且误报率低。     

Cascaded spiral microfluidic device for deterministic and high purity continuous separation of circulating tumor cells

Inertial microfluidics is an emerging class of technologies developed to separate circulating tumor cells (CTCs). However, defining design parameters and flow conditions for optimal operation remains nondeterministic due to incomplete understanding of the mechanics, which has led to challenges in designing efficient systems. Here, we perform a parametric study of the inertial focusing effects observed in low aspect ratio curvilinear microchannels and utilize the results to demonstrate the isolation of CTCs with high purity. First, we systematically vary parameters including the channel height, width, and radius of curvature over a wide range of flow velocities to analyze its effect on size dependent differential focusing and migration behaviors of binary (10 μm and 20 μm) particles. Second, we use these results to identify optimal flow regimes to achieve maximum separation in various channel configurations and establish design guidelines to readily provide information for developing spiral channels tailored to potentially arbitrary flow conditions that yield a desired equilibrium position for optimal size based CTC separation. Finally, we describe a fully integrated, sheath-less cascaded spiral microfluidic device to continuously isolate CTCs. Human breast cancer epithelial cells were successfully extracted from leukocytes, achieving 86.76% recovery, 97.91% depletion rate, and sustaining high viability upon collection to demonstrate the versatility of the device. Importantly, this device was designed without the cumbersome trail-and-error optimization process that has hindered the development of designing such inertial microfluidic systems.     

Improved asynchronous stabilization method for nonhomogeneous Markovian jump fuzzy systems with incomplete transition rates

This paper proposes an improved asynchronous stabilization method for nonhomogeneous Markovian jump fuzzy systems (MJFSs) with incomplete transition rates via a nonparallel distributed compensation (non-PDC) control scheme. To cover a more realistic situation in the continuous-time MJFS domain, this paper focuses on addressing the following issues differently from previous studies: 1) emergence of a nonhomogeneous Markov process and asynchronous control mode, 2) separation of the Lyapunov matrix from the control gain within stabilization conditions, and 3) relaxation of stabilization conditions subject to multiple time-varying parameters. Specifically, the effects of nonhomogeneity and asynchronism are simultaneously reflected in the stabilization conditions, and separation and relaxation techniques are additionally developed as needed. Finally, the advantages of our method are illustrated through two examples: the first is provided to show the effectiveness of the proposed separation technique, and the second is provided to show that the relaxed stabilization conditions are less conservative than previous results.     

Stochastic finite-time stabilization for discrete-time positive Markov jump time-delay systems

In this paper, the problems of stochastic finite-time stability and stabilization of discrete-time positive Markov jump systems are investigated. To deal with time-varying delays and switching transition probability (STP), stochastic finite-time stability conditions are established under mode-dependent average dwell time (MDADT) switching signal by developing a stochastic copositive Lyapunov-Krasovskii functional approach. Then a dual-mode dependent output feedback controller is designed, thus stochastic finite-time stabilization is achieved based on linear programming technique. Finally, two examples are given to show the effectiveness of our results.     

Quantized control of event-triggered networked systems with time-varying delays

The paper is a study of quantized control for stochastic Markov jump systems with interval time-varying delays and bounded system noise under event-triggered mechanism. A new scheme of Lyapunov–Krasovskii functional which contains the quadratic terms and integral terms is presented. Then quadratic convex technology, the theory of stochastic switching system, and logarithmic quantizer are applied to this paper. The design of quantized controller is obtained with those methodologies. Different from previous results, our derivation applies the idea of second-order convex combination. The conservatism of stability criteria for systems is reduced by using this method. A numerical example under different conditions is given to demonstrate the effectiveness and validity of the new design techniques.