计算矩阵主平方根和符号函数的递推算法及其稳定性

一、引言 矩阵的主平方根和矩阵符号函数在控制理论中有许多用途。例如求解矩阵的李亚普诺夫方程和矩阵的黎卡提方程,大规模系统的降阶和离散系统模型——连续系统模型的转换等。常用的矩阵开方的算法有:从矩阵连分式导出的矩阵开方算法,利用Newton-Raphson法得到的矩阵开方算法以及从矩阵符号函数导出的矩阵开方算     

切换系统的二类共同Lyapunov 函数

研究切换系统的共同Lyapunov函数存在问题.对于一类正切换系统,给出了共同Lyapunov函数存在的充分条件.当系统矩阵集为二阶矩阵紧集时,给出了判断共同Lyapunov函数存在的方法,并给出了计算共同Lyapunov函数的算法.最后通过算例验证了所提出算法的有效性.     

基于目标函数的递推子空间辨识算法

针对实际工程中要求对系统参数进行在线估计的问题, 提出一种递推子空间辨识的新方法. 通过引入辅助变量关系将递推子空间辨识问题转化为目标函数的迭代最小化问题. 采用递推最小二乘算法在线估计参数并由传播方法得到更新的广义能观性矩阵, 进而求得子空间辨识模型系统参数. 该算法简单有效且对初值具有鲁棒性. 最后, 通过仿真实例验证算法的有效性.     

一种能同时获得模型阶次和参数的递推辨识算法

对SISO线性差分方程模型,可以构造一种新的数据乘积矩矩阵,称信息压缩阵.对信息 压缩阵进行递推UD分解,便得到一种新的递推辨识算法,它能在每步递推中同时得到模型 的阶次和参数,从而降低了辨识过程的计算量.该方法还同时具有良好的数值计算品质.     

六元一阶相关免疫函数的新计数算法

若布尔函数的输出不泄漏其输入值的有关信息,则该函数是相关免疫的。该文基于列平衡矩阵研究相关免疫函数的计数问题,利用穷举和统计相结合的方法对2k×6(0≤k≤16)阶定序列平衡矩阵进行计数,给出一种新的六元一阶相关免疫函数的计数算法。与同类算法相比,新算法的复杂度降为(224),大大提高了一阶相关免疫函数的计数效率。     

高阶矩量法的超级电磁计算研究

矩量法是广泛使用的高精度电磁数值算法之一。在仿真复杂电磁问题时,该算法需要处理大型复数稠密矩阵方程,这导致其面临内存需求高、计算时间长的问题。与传统基函数相比,本文采用的高阶多项式基函数能够在保证计算精度的前提下大幅度降低未知量,进而降低矩阵阶数。在此基础上,本文设计了基于分块矩阵的高效并行策略,在国内超级计算机平台开展了并行高阶矩量法的超级电磁计算研究,大幅度提升了矩量法的仿真能力。在国产神威蓝光超级计算机上,以机载天线阵列的辐射特性计算为例,对并行规模高达30720 CPU核时的算法性能进行了评估,测试结果表明算法在并行规模扩大20倍以上时仍可获得50%以上的并行效率。在当前排名世界第一的天河2号超级计算机上,以飞机散射特性计算为例,对并行规模高达201600 CPU核时的算法性能进行了评估,测试结果表明算法在并行规模扩大约8倍时可获得50%以上的并行效率。数值仿真结果表明并行高阶矩量法可以在不同架构的超级计算机上高效完成复杂电大目标的精确电磁计算。     

一阶系统自伴随条件和Lagrange函数的构造

重新研究一阶系统变分法逆问题,修正了某些文献关于一阶微分方程组自伴随条件的失误,导出了把一阶系统化为自伴随形式的变换矩阵所满足的方程,列出了构造自伴随一阶系统Lagrange函数的两种方法.举例说明所得结果的应用.     

一类非线性广义马尔可夫跳变系统的耗散控制

将耗散理论的二次型供给率中的矩阵Q推广到正定的情况.进而研究了在状态转移概率未知的情况下一类连续时间非线性广义马尔可夫跳变系统的严格耗散控制问题.在应用范围更广的Willems耗散性定义的基础上,首先基于一类Lyapunov函数,给出了相应的随机容许的条件,然后设计导数比例反馈控制器,通过一系列的矩阵构造和合同变换,将双线性矩阵不等式(BMI)转化为可用LMI工具箱解决的线性矩阵不等式(LMI).最后通过数值算例并结合Matlab给出实例,证明其可行性.     

时滞离散系统最优输出跟踪控制的灵敏度法

针对具有有限时间二次型性能指标的时滞离散系统,研究了最优输出跟踪控制问题.通过引入一个灵敏度参数,将原最优输出跟踪控制问题转化为不含超前项和时滞项的一族两点边值问题.得到的最优输出跟踪控制律由状态向量的线性解析函数和伴随向量级数形式的补偿项组成,其解析函数由一次性求解R iccati矩阵差分方程和矩阵差分方程得到,补偿项由求解伴随向量差分方程的递推公式得到.仿真结果表明了该方法的有效性.     

按段多重契比雪夫多项式系及其在线性时变系统辨识中的应用

本文在块脉冲函数系和契比雪夫多项式系基础上定义了一种新的正交函数系--按段多 重契比雪夫多项式系,研究该函数系的主要性质和基本运算法则,得出了积分运算矩阵、乘积 运算矩阵和元素乘积运算矩阵,并用此函数系研究线性时变系统的参数辨识问题,获得了简 单、快速、高精度的递推辨识算法.数值例子计算结果表明,当采用如伪随机信号一类的充分 激励的函数作为被辨识系统的试验信号,本文提出的算法所得结果的精度和计算时间都比一 般正交契比雪夫多项式算法所得结果为好.     

一种奇序列并行排序算法

提出了一种奇序列双调排序算法，通过分析发现，该算法对某些奇双调序列不能得到正确的排序结果。在该算法的基础上，通过增加CCI操作，得到一种改进算法，改进后的算法能对任意奇双调序列进行正确排序，且不增加存储空间，计算复杂度级别也不变。     

Efficient and scalable quicksort on a linear array with a reconfigurable pipelined bus system

Based on the current fiber optic technology, a new computational model, called a linear array with a reconfigurable pipelined abus system (LARPBS), is proposed in this paper. A parallel quicksort algorithm is implemented on the model, and its time complexity is analyzed. For a set of N numbers, the quicksort algorithm reported in this paper runs in O(log₂ N) average time on a linear array with a reconfigurable pipelined bus system of size N. If the number of processors available is reduced to P, where P < N, the algorithm runs in O((N/P) log₂ N) average time and is still scalable. Besides proposing a new algorithm on the model, some basic data movement operations involved in the algorithm are discussed. We believe that these operations can be used to design other parallel algorithms on the same model. Future research in this area is also identified in this paper.     

一种基于代表元的划分算法

划分是把程序中不同的计算和数据分配到并行处理系统的不同处理机来充分利用并行系统的计算资源、提高程序处理速度的一种优化技术.划分的效果对程序在并行系统上的执行效率将产生至关重要的影响,因此划分问题一直是并行领域研究的一个热点.但是应用程序的一些特性,如非紧密嵌套循环、一条语句对非只读数组的多次引用间存在重叠、不同语句对同一数组不同步长的引用,给有效解决划分问题设置了极大的障碍.已有的划分算法无法对具有这些特征的程序进行自动划分.虽然在对具有这些特征的程序进行手工优化过程中,存在一些直观上的划分策略,但这些策略无法应用到编译器中来指导编译器完成对程序的自动划分.文中根据这类程序的特点,提出了一种基于代表元的划分算法.该算法通过使用程序中对划分计算产生实际影响的数组引用作为代表元素构造各种划分的限制条件,完成程序的划分.同时通过寻找最大一致性数据划分方向有效减少了程序划分过程中的数据重组织通信.该算法已经在AFT2004中实现,并对应用程序获得了很好的效果.     

On scalarized calculation of the likelihood function in array square-root filtering algorithms

An efficient method of scalarized calculation of the logarithmic likelihood function based on the array square-root implementation methods for Kalman filtering formulas was proposed. The algorithms of this kind were shown to be more stable to the roundoff errors than the conventional Kalman filter. The measurement scalarization technique enables a substantial reduction in the computational complexity of the algorithm. Additionally, the new implementations are classified with the array filtering algorithms and thereby are oriented to the parallel calculations. Computational results corroborated effectiveness of the new algorithm.     

Swarm-based intelligent optimization approach for layout problem

Layout problem is a kind of NP-Complete problem. It is concerned more and more in recent years and arises in a variety of application fields such as the layout design of spacecraft modules, plant equipment, platforms of marine drilling well, shipping, vehicle and robots. The algorithms based on swarm intelligence are considered powerful tools for solving this kind of problems. While usually swarm intelligence algorithms also have several disadvantages, including premature and slow convergence. Aiming at solving engineering complex layout problems satisfactorily, a new improved swarm-based intelligent optimization algorithm is presented on the basis of parallel genetic algorithms. In proposed approach, chaos initialization and multi-subpopulation evolution strategy based on improved adaptive crossover and mutation are adopted. The proposed interpolating rank-based selection with pressure is adaptive with evolution process. That is to say, it can avoid early premature as well as benefit speeding up convergence of later period effectively. And more importantly, proposed PSO update operators based on different versions PSO are introduced into presented algorithm. It can take full advantage of the outstanding convergence characteristic of particle swarm optimization (PSO) and improve the global performance of the proposed algorithm. An example originated from layout of printed circuit boards (PCB) and plant equipment shows the feasibility and effectiveness of presented algorithm.     

Flexible rerouting schemes for reconfiguration of multiprocessor arrays

In a multiprocessor array, some processing elements (PEs) fail to function normally due to hardware defects or soft faults caused by overheating, overload or occupancy by other running applications. Fault-tolerant reconfiguration reorganizes fault-free PEs to a new regular topology by changing the interconnection among PEs. This paper investigates the problem of constructing as large as possible logical array with short interconnects from a physical array with faults. A flexible rerouting scheme is developed to improve the efficiency of utilizing fault-free PEs. Under the scheme, two efficient reconfiguration algorithms are proposed. The first algorithm is able to generate the maximum logical array (MLA) in linear time. The second algorithm reduces the interconnect length of the MLA, and it is capable of producing nearly optimal logical arrays in comparison to the lower bound of the interconnect length, that is also proposed in this paper. Experimental results validate the efficiency of the flexible rerouting schemes and the proposed algorithms. For 128×128 host arrays with 30% unavailable PEs, the proposed approaches improve existing algorithm up to 44% in terms of logical array size, while reducing the interconnection redundancy by 49.6%. In addition, the proposed algorithms are more scalable than existing approaches. On host arrays with 50% unavailable PEs, our algorithms can produce logical arrays with harvest over 56% while existing approaches fail to construct a feasible logical array.     

基于最小冗余线阵的二维DOA估计方法

针对传感器阵列二维DOA估计中阵元数较多且阵元利用率较低的问题,提出了一种低阵元冗余的二维DOA估计方法.该方法通过在最小冗余线阵基础上添加两个导向阵元的方法,将最小冗余线阵的应用拓展到二维DOA估计.同时该方法利用多个时延的阵元输出共轭循环相关函数构造"伪数据阵",在时空域中等效出两个具有旋转不变性的平行子阵,进而运用DOA矩阵法估计信号二维DOA.该方法不仅避免了最优时延选择问题,继承了DOA矩阵法无需谱峰搜索且无需二维角度参数配对等优点.还用较少的阵元获得了较大的阵列有效孔径.仿真结果表明,该方法与CCDM算法相比具有更好的低信噪比适应能力和稳健性.     

Robust DOA estimation and array calibration in the presence of mutual coupling for uniform linear array

The presence of unknown mutual coupling between array elements is knownto significantly degrade the performance of most high-resolution direction of arrival (DOA)estimation algorithms. In this paper, a robust subspace-based DOA estimation and arrayauto-calibration algorithm is proposed for uniformly linear array (ULA), when the arraymutual coupling is present. Based on a banded symmetric Toeplitz matrix model for themutual coupling of ULA, the algorithm provides an accurate and high-resolution DOAestimate without any knowledge of the array mutual couplings. Moreover, a favorableestimate of mutual coupling matrix can also be achieved simultaneously for arrayauto-calibration. The algorithm is realized just via one-dimensional search or polynomialrooting, with no multidimensional nonlinear search or convergence burden involved. Theproblem of parameter ambiguity, statistically consistence and efficiency of the newestimator are also analyzed. Monte-Carlo simulation results are also provided todemonstrate the     

An optimal parallel algorithm for sparse matrix bandwidth reduction on a linear array

A simple and efficient algorithm for the bandwidth reduction of sparse symmetric matrices is proposed. It involves column-row permutations and is well-suited to map onto the linear array topology of the SIMD architectures. The efficiency of the algorithm is compared with the other existing algorithms. The interconnectivity and the memory requirement of the linear array are discussed and the complexity of its layout area is derived. The parallel version of the algorithm mapped onto the linear array is then introduced and is explained with the help of an example. The optimality of the parallel algorithm is proved by deriving the time complexities of the algorithm on a single processor and the linear array.