基于径向基函数网络或模糊系统的非线性连续时间系统的自适应调节

对于一类连续时间的非线性动态系统x=f(x)+Bu+d,当系统中的非线性函数f(x)满足有界或线性增长条件(具有未知的增长系数)时,首先证明了f(x)中的x落入一紧集中,然后根据径向基函数网络或模糊系统的逼近性质,给出了两种自适应调节器的设计方法.利用李亚普诺夫稳定性理论,证明了控制算法是全局稳定的,闭环系统的状态是一致最终有界的,且控制律是稳定的.     

基于调频傅里叶变换的匀加速转动目标ISAR成像

现有匀加速旋转目标逆合成孔径雷达(inverse synthetic aperture radar, ISAR)成像方法通常采用二维搜索估计目标转动参数,从而导致计算量大。提出一种基于调频傅里叶变换的ISAR成像方法。该方法利用目标散射点回波相位二次项系数与一次项系数的比值仅取决于目标转动参数这一特点,通过搜索调频傅里叶变换的调频系数使目标横向像熵值最小,得到该比值的估计结果,避免了二维搜索导致的计算量大的问题。然后对各距离单元回波作相应的调频傅里叶变换,即可得到聚焦良好的ISAR像。仿真结果验证了该方法的有效性。     

基于模糊逻辑的一类复杂系统全息控制设计

针对一类结构上具有相似性的非线性不确定复杂系统,利用模糊逻辑系统可以充分逼近连续函数的性质,研究这类复杂系统的鲁棒镇定问题,设计出了系统的全息鲁棒控制器和模糊逻辑系统参数估计的自适应律。为了简化控制器结构,在构造模糊逻辑系统时对被控系统的不确定性进行了归一化处理。在较弱的假设条件下,证明了这种控制器使被控系统的状态及参数估计误差一致终极有界,同时给出了误差的严密的数学分析。仿真实例表明所提出的方法是有效的。     

多移动机器人圆形队列形成算法

该文提出一种多移动机器人圆形队列形成算法。在机器人数量不太大的条件下,通过迭代调节多机器人形成的多边形的边长和内角以实现在某一圆上均匀分布,再调节机器人与圆心的距离,最终使机器人均匀分布在一个指定半径的圆上。仿真结果验证了该算法的有效性。     

SOME INITIAL-OBLIQUE DERIVATIVE BOUNDARY VALUE PROBLEM FOR QUASILINEAR PARABOLIC EQUATIONS WITH UNBOUNDED COEFFICIENTS

1 IntroductionThis paper is concerned with the a priori estimates and the ekistence of solutions of theinitiaLoblique derivative boundary value problem for quasilinear non-divergence parabolic equa-tions as follows:where O is a bounded domain in R"(N > 2) with smooth boundary 0a e C' ', QT =[o,T) x a be the parabolic domain in H" ,, ST = [o,T) x aa is the lateral boundary, andarQT is the parabolic boundary of QT' The repeated indices means summatiOns from 1 to N.In [11, the first bounda…     

内P-集合与F-内嵌入信息发现-辨识

P-集合是由内P-集合X^F 与外P-集合X^F 构成的有序集合对,它具有动态特性。利用内P-集合X^F,给出F-内嵌入信息(x)^F、F-内嵌入系数IEC(x)^F 与F-内嵌入度IED(x)^F的概念,得到F-内嵌入信息存在性定理、依赖关系定理与可辨识性定理。在这些概念与结果的基础上,给出F-内嵌入信息在目标搜索中的应用。     

指数寿命产品的寿命性能评估

传统的统计过程控制理论假设过程的质量特性值服从正态分布,然而在实践过程中这一假设并不成立。本文假设产品的质量特性值服从指数分布,基于定数截尾样本,用过程能力指数评估产品的寿命性能,给出寿命性能指数CL的一致最小无偏估计及其置信区间,提出一种新的方法对CL进行检验。最后通过实例表明,此检验方法不仅简单易行,而且还可以用来判断产品是否达到所要求的水平。     

OPTIMAL AND ROBUST DETECTION OF MULTIVARIATE OUTLIERS FOR ELLIPTICALLY CONTOURED DISTRIBUTION

The outlier problem for a multivariate elliptically contoured distribu-tion's random sample with mean slippage is defined and the likelihood ratio test ofthe null hypothesis,in which there are no outliers,versus the alternative hypothesis,in which some outliers are present,is derived.We show that the testing problemis invariant under a group of affine transformations and obtain the maximal in-variance which is equivalent to the likelihood ratio testing statistic.Furthermore,the non-null and null density distribution functions of the likelihood ratio testingstatistic are derived.We find that the null density distribution function of thetesting statistic is robust and the density distribution function is a monotonicallikelihood ratio function of the maximal invariance.Therefore,the likelihood ratiotest is a uniformly most powerful invariant test among the group of affine transfor-mations.In the last section,we give an example of detecting multivariate outliersin elliptically contoured distribution.     

SMOOTH PL-ESTIMATOR OF DISTRIBUTION FUNCTION UNDER RANDOM TRUNCATION DATA

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GLOBAL CONVERGENCE OF THE DAI-YUAN CONJUGATE GRADIENT METHOD WITH PERTURBATIONS

In this paper, the authors propose a class of Dai-Yuan （abbr. DY） conjugate gradient methods with linesearch in the presence of perturbations on general function and uniformly convex function respectively. Their iterate formula is xk＋1 = xk ＋ αk（sk ＋ ωk）, where the main direction sk is obtained by DY conjugate gradient method, ωk is perturbation term, and stepsize αk is determined by linesearch which does not tend to zero in the limit necessarily. The authors prove the global convergence of these methods under mild conditions. Preliminary computational experience is also reported.     

基于后推技术的直接鲁棒自适应模糊控制

针对一类带摄动的严格反馈非线性系统,基于后推设计方法,利用第一类模糊系统的逼近能力,提出了一种新的直接自适应控制方案。该方案中引入连续鲁棒项对系统的摄动部分进行抑制,并在自适应律中利用了leakage项以防止参数漂移。通过理论分析,证明了闭环系统是半全局一致终结有界的,跟踪误差收敛到一个小的残差集内。仿真结果表明了该方法的有效性。     

基于模糊逻辑系统的组合大系统自适应观测器设计

针对一类非线性不确定组合大系统，利用模糊逻辑系统具有充分逼近连续函数的性质，分析和研究了这类系统自适应状态观测器设计问题，并在较弱的假设条件下，证明这种观测器与被控系统状态间的误差及各参数估计误差一致终极有界。最后的仿真实例说明了本文所提出方法的有效性。     

STRONG CONVERGENCE THEOREMS FOR NONEXPANSIVE MAPPING

This paper introduces a composite iteration scheme for approximating a fixed point of nonexpansive mappings in the framework of uniformly smooth Banach spaces and the reflexive Banach spaces which have a weakly continuous duality map, respectively, we establish the strong convergence of the composite iteration scheme. The results improve and extend those of Kim, Xu, Wittmann and some others.     

Robust极点配置及其优化算法

本文提出了一个线性系统极点配置的有效算法,首先利用正交变换将能控系统简化成上Hessenberg能控标准型,然后利用(A,B)特征子空间找出闭环系统关于指定复数集所有可能的特征向量,从中选取一组线性无关的向量{x_1,…x_n}作为闭环系统的特征向量,使得max{c_k,k∈n}极小,最后由x={x_1,…x_n}找出反馈阵F,使得闭环系统(A+BF,B)的极点集等于L。     

A delayed ratio-dependent predator-prey system with stage-structured and impulsive effect

In this paper, a delayed ratio-dependent Holling-III predator-prey system with stagestructured and impulsive stocking on prey and continuous harvesting on predator is considered. The authors obtain sufficient conditions of the global attractivity of predator-extinction periodic solution and the permanence of the system. These results show that the behavior of impulsive stocking on prey plays an important role for the permanence of the system. The authors also prove that all solutions of the system are uniformly ultimately bounded. The results show that the biological resource management is effective and reliable.     

模糊离散动力系统的一致稳定性

考察如下模糊离散动力系统$X^{( k+1)} =AX^{( k)}$ ( 1 )其中 A为 n阶模糊方阵 ,系统初态 $X^{(0)}$ 为 n维模糊向量 ,$AX^{( k)}$ 为 max-T意义下模糊矩阵的乘积 ,T为三角模 .证明了如果三角模 T连续 ,则任意形如 ( 1 )的模糊离散动力系统的平衡态在 Lyapunov意义下都是一致稳定的 .以实例说明了即使三角模 T是上半连续的 ,也存在形如 ( 1 )的模糊离散动力系统 ,使其某个平衡态在 Lyapunov意义下不稳定.     

反向误差传播的学习策略

本文探讨多层神经网络、反向误差传播学习过程收敛缓慢的原因,提出了修改后的激励函数(x),变步长策略,输出反馈抑制策略及模式矢量预处理,从而大大加速了学习收敛过程。还给出了计算机模拟的结果。     

Convergence of Distributed Gradient-Tracking-Based Optimization Algorithms with Random Graphs

This paper studies distributed convex optimization over a multi-agent system, where each agent owns only a local cost function with convexity and Lipschitz continuous gradients. The goal of the agents is to cooperatively minimize a sum of the local cost functions. The underlying communication networks are modelled by a sequence of random and balanced digraphs, which are not required to be spatially or temporally independent and have any special distributions. The authors use a distributed gradient-tracking-based optimization algorithm to solve the optimization problem. In the algorithm,each agent makes an estimate of the optimal solution and an estimate of the average of all the local gradients. The values of the estimates are updated based on a combination of a consensus method and a gradient tracking method. The authors prove that the algorithm can achieve convergence to the optimal solution at a geometric rate if the conditional graphs are uniformly strongly connected, the global cost function is strongly convex and the step-sizes don't exceed some upper bounds.     

THE GOODNESS-OF-FIT TEST BY USING MULTIVARIATE RANDOM WEIGHTING METHOD

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