数字图像的Caputo分数阶微分增强

近年来基于分数阶微积分的信号和图像处理受到广泛关注. 目前常见的应用于图像处理的分数阶微分算子包括G-L（Grünwald-Letnikov）型、R-L（Riemann-Liouville）型和Caputo型3种.G-L和R-L算子尽管能对图像有着一定的增强效果,但其对图像对比度、清晰度的提升有限;而Caputo型微分掩模算子目前多限于（0,1）阶的低阶算子,其高阶次算子的研究和应用相对较少.对高阶次Caputo型分数阶微分算子及其图像增强应用进行研究,首先针对（1,2）阶、（2,3）阶次Caputo型分数阶微分构建一种基于向前差分的微分掩模算子,并对其误差进行了论证;其次进一步给出了更高阶次Caputo型分数阶微分算子的矩阵化表现形式;最后在此基础上将所提出的高阶次Caputo型分数阶微分掩模算子应用于图像增强.实验结果表明所提出的高阶次Caputo型分数阶微分算子取得了很好的图像增强效果,对提升图像的对比度、清晰度和平均梯度具有较为明显的优势.

     

Learning-Based Switched Reliable Control of Cyber-Physical Systems With Intermittent Communication Faults

This study deals with reliable control problems in data-driven cyber-physical systems(CPSs) with intermittent communication faults, where the faults may be caused by bad or broken communication devices and/or cyber attackers. To solve them, a watermark-based anomaly detector is proposed, where the faults are divided to be either detectable or undetectable.Secondly, the fault's intermittent characteristic is described by the average dwell-time(ADT)-like concept, and then the reliable control issues, under the undetectable faults to the detector, are converted into stabilization issues of switched systems. Furthermore,based on the identifier-critic-structure learning algorithm, a datadriven switched controller with a prescribed-performance-based switching law is proposed, and by the ADT approach, a tolerated fault set is given. Additionally, it is shown that the presented switching laws can improve the system performance degradation in asynchronous intervals, where the degradation is caused by the fault-maker-triggered switching rule, which is unknown for CPS operators. Finally, an illustrative example validates the proposed method.     

基于微分算子小波显式表示的分布参数系统最优逼近控制

基于微分算子在紧支撑正交小波基下的精确显式表示，给出了一种分布参数系统最优控制的逼近计算方法．将微分算子投影到小波空间，利用其矩阵表示形式，将分布参数系统的最优控制转化为集中参数系统最优控制问题．该方法不需要为边界条件重新构造基函数，在将偏微分方程转化为其常微分方程近似形式的过程中，不需要考虑边界条件的影响，因此计算方便、适用范围广，同时具有很高的精度和计算效率,可以对计算误差进行预测．利用该方法进行了基于Daubechies (db1)小波的仿真计算，并对计算结果进行了验证．     

利用1~2阶分数阶微分掩模的边缘检测

现有的分数阶微分边缘检测算子大都是基于0~1阶分数阶微分而构造,鲜有文献讨论基于1~2阶分数阶微分的边缘检测算子。为此,分析了1~2阶分数阶微分对信号的作用,基于1~2阶分数阶微分构造了一种新的边缘检测掩模算子。实验结果表明,该算子不仅优于常用整数阶微分算子,而且比现有的一些0~1阶分数阶微分算子具有更好的边缘检测效果。     

Relationship Between Integer Order Systems and Fractional Order Systems and Its Two Applications

Existence of periodic solutions and stability of fractional order dynamic systems are two important and difficult issues in fractional order systems (FOS) field. In this paper, the relationship between integer order systems (IOS) and fractional order systems is discussed. A new proof method based on the above involved relationship for the non existence of periodic solutions of rational fractional order linear time invariant systems is derived. Rational fractional order linear time invariant autonomous system is proved to be equivalent to an integer order linear time invariant non-autonomous system. It is further proved that stability of a fractional order linear time invariant autonomous system is equivalent to the stability of another corresponding integer order linear time invariant autonomous system. The examples and state figures are given to illustrate the effects of conclusion derived.      

复杂分数阶多自主体系统的运动一致性

复杂环境中,许多自然现象的动力学特性不能应用整数阶方程描述,而只能用分数阶（非整数阶）动力学的智能个体合作行为来解释. 本文假设多自主体 系统存在个体差异,采用不同的分数阶动力学特性组成复杂分数混合阶微分方程. 应用分数阶系统的Laplace变换和频域理论,研究了有向网络拓扑下,时延分数混合阶多自主体系统的运动一致性. 由于整数阶系统是分数阶系统的特殊情况,本文的结论可以推广到整数阶与分数阶混合的多自主体系统中. 最后,应用仿真实例对本文结论进行了验证.     

基于元算子的深度学习框架缺陷检测方法

在用于构建深度学习模型的深度学习框架中,算子的正确计算对于深度学习模型的正确预测至关重要.然而,已有的深度学习框架缺陷检测方法只能通过比较和推测的方式找到不同深度学习框架之间计算结果相差较大的算子,而且无法检测深度学习模型在训练过程中产生的计算错误,具有很大的局限性.针对此问题,本文设计并实现了基于元算子的深度学习框架...     

整数阶滤波的分数阶Sobel算子的边缘检测算法

针对传统的整数阶微分图像边缘检测算子存在的边缘模糊不清、受噪声影响大等问题,该算法从改进传统的整数阶微分Sobel算子入手,以分数阶微分理论为基础推导出了分数阶微分Sobel算子,结合Sobel算子边缘检测方法,将整数阶微分Sobel算子作为滤波器与分数阶微分Sobel算子作卷积运算,改进了整数阶微分Sobel算子。整数阶微分滤波后的分数阶微分Sobel算子成功地解决了传统的边缘检测算子存在的准确性低、抗噪性差等问题。理论研究与实验结果表明,该边缘检测算子对图像的边缘细节特征刻画得更精细,抗噪性更强,优于常用的整数阶微分边缘检测算子,边缘检测效果很好。     

基于Riemann-Liouville改进的1~2阶分数阶边缘提取新模型

针对数字图像的处理中采用整数步长与0~1阶分数阶微分的掩模算子未能精确定位边缘信息、缺少图像的纹理细节的问题,在Laplacian算子的基础上提出了一种新的边缘检测掩模算子。该算法从Riemann-Liouville(R-L)定义出发,推出1~2阶分数阶微分在中频信号的增强效果优于0~1阶分数阶微分并显著提升了高频信号,最终得到精确的检测效果。仿真结果表明:提出的算子能更好地提取边缘信息,尤其对灰度变化不大的平滑区域中纹理细节丰富的图像,该算子检测到的信息优于现有0~1阶微分算子,针对主观识别有更高的准确率;客观上采用扫描法的定位误差统计,该算子的综合定位误差率为7.41%,低于整数阶微分算子(最低为10.36%)与0~1阶微分算子(最低为9.97%),有效提高了边缘定位精度。该算子尤其适用于具有较高频信息的图像边缘检测中。     

闭包算子与邻域系的广义化

通过弱化一般拓扑中的闭包算子公理,引入了广义闭包算子的概念,研究了其与稍早引入的广义邻域系的关系。特别的,证明了二者之间存在着自然的完备格同构。     

Trajectory Controllability of Fractional Integro‐Differential Systems in Hilbert Spaces

In this paper, sufficient conditions for trajectory controllability of nonlinear fractional integro‐differential systems involving Caputo fractional derivative of order α∈(1,2] in finite and as well as in infinite dimensional Hilbert spaces are obtained. Our tools of study include set‐valued functions, theory of monotone operators and α‐order cosine family of operators. The main results are well illustrated with the aid of examples.     

基于反向累积法的强化缓冲算子序列的研究

在灰色系统理论缓冲算子公理体系下,利用反向累积和的概念.构造了l阶反向累积和算术平均强化缓冲算子及l阶反向累积和几何平均强化缓冲算子.给出并证明了其强化缓冲算子的性质和算子作用后序列之间的大小关系.该类算子具有普适性,当阶数等于1时即为党氏强化缓冲算子.最后通过一个实例验证了该算子的有效性.     

The h‐Difference Approach to Controllability and Observability of Fractional Linear Systems with Caputo–Type Operator

In the paper a class of h‐difference linear control systems with n fractional orders is studied. The Caputo‐type h‐difference operator is used. The formula of the solution to the stated initial value problem of the given system is proved. The problems of controllability and observability in a finite number of steps of h‐difference linear control systems with n fractional orders are studied.     

信息物理融合系统网络安全综述

信息物理融合系统（cyber-physical systems， CPS）是集计算、通信和控制于一体的智能系统，实现网络和物理的深度协作和有机融合.目前CPS在关键的基础设施、政府机构等领域发挥着越来越重要的作用.由于物理限制，计算机和网络产生的安全漏洞会导致CPS遭受巨大的破坏，同时还会引起经济损失、社会动乱等连锁反应，所以研究CPS的安全问题对于确保系统安全运行具有重要意义.本文结合国内外的研究现状，概述了CPS安全控制和攻击检测的最新进展.首先本文总结了CPS典型的系统建模以满足对系统性能分析的需要.然后介绍了3种典型的网络攻击，即拒绝服务攻击、重放攻击和欺骗攻击.根据检测方法的类别，对CPS攻击检测的发展进行的概述.此外还讨论了系统的安全控制和状态估计.最后总结和展望了CPS网络安全面临的挑战和未来的研究方向.     

Set based logic programming

In a previous paper (Blair et al. 2001), the authors showed that the mechanism underlying Logic Programming can be extended to handle the situation where the atoms are interpreted as subsets of a given space X. The view of a logic program as a one-step consequence operator along with the concepts of supported and stable model can be transferred to such situations. In this paper, we show that we can further extend this paradigm by creating a new one-step consequence operator by composing the old one-step consequence operator with a monotonic idempotent operator (miop) in the space of all subsets of X, 2 ^X . We call this extension set based logic programming. We show that such a set based formalism for logic programming naturally supports a variety of options. For example, if the underlying space has a topology, one can insist that the new one-step consequence operator always produces a closed set or always produces an open set. The flexibility inherent in the semantics of set based logic programs is due to both the range of natural choices available for specifying the semantics of negation, as well as the role of monotonic idempotent operators (miops) as parameters in the semantics. This leads to a natural type of polymorphism for logic programming, i.e. the same logic program can produce a variety of outcomes depending on the miop associated with the semantics. We develop a general framework for set based programming involving miops. Among the applications, we obtain integer-based representations of real continuous functions as stable models of a set based logic program.      

Some geometric aggregation operators based on intuitionistic fuzzy sets

The weighted geometric (WG) operator and the ordered weighted geometric (OWG) operator are two common aggregation operators in the field of information fusion. But these two aggregation operators are usually used in situations where the given arguments are expressed as crisp numbers or linguistic values. In this paper, we develop some new geometric aggregation operators, such as the intuitionistic fuzzy weighted geometric (IFWG) operator, the intuitionistic fuzzy ordered weighted geometric (IFOWG) operator, and the intuitionistic fuzzy hybrid geometric (IFHG) operator, which extend the WG and OWG operators to accommodate the environment in which the given arguments are intuitionistic fuzzy sets which are characterized by a membership function and a non-membership function. Some numerical examples are given to illustrate the developed operators. Finally, we give an application of the IFHG operator to multiple attribute decision making based on intuitionistic fuzzy sets.     

用分数阶微分提取图像边缘

文章是分数阶微分在图像处理中的尝试性应用。首先通过理论上分析得出分数阶微分可以大幅提升信号高频成分,增强信号的中频成分,非线性保留信号的甚低频。据此分析得出分数阶微分应用于图像边缘信息提取将获得高于传统基于一、二阶微分的方法的信噪比。然后由经典的分数阶微分定义出发,推导出了分数阶差分方程,构建了近似的分数阶Tiansi微分模板。最后通过图像边缘提取的实验表明：基于分数阶微分算子不仅可以有效提取图像边缘,而且比整数阶微分算子具有更高的信噪比。为拓展分数阶微分的应用领域,进行了有意义的探索。