On Optimal Dyadic Linear Prediction and Filtering in the Sequency Domain

In this paper dyadic linear prediction and dyadic linear filtering on a dyadic generalizedstationary random process are dealt with via the Walsh transform.Taking the minimum of themean-square error     

结构元线性生成的模糊线性微分系统

主要目的是利用模糊结构元方法来解决模糊线性微分系统的模糊初值问题.首先，简单地介绍了模糊结构元方法，根据该方法定义了线性生成的模糊线性微分系统.其次，利用由模糊结构元线性表示的模糊值函数和模糊值函数的导数，研究了模糊线性微分系统的求解问题，给出了系统解存在的充要条件.最后，将给出一个实际例子，进一步表明了该方法的有效性.     

线性组合预测模型优化问题研究

从线性组合预测模型绝对误差序列出发,对线性组合预测模型的精度特征进行描述和分析,系统地研究线性组合预测模型的优化方法,为线性组合预测模型的优化设计提供理论基础。     

含直觉模糊弹性约束的模糊线性规划求解

本文基于模糊结构元方法构建并讨论了一类含有直觉模糊弹性约束的新型模糊线性规划问题. 通过引入模糊数的加权特征数, 定义了一种序关系并拓展了Verdegay的模糊线性规划方法, 将新型模糊线性规划问题转化成两个等价的含参数约束条件的清晰线性规划模型, 给出了此类线性规划模型对比最优可行解的求法. 最后通过一个数值实例来说明此类问题的一般求解方法.     

Boole函数的稳健线性可分及其计数

Ｂｏｏｌｅ函数的线性可分和线性不可分问题，一直是前向人工神经网络的一个比较困难的问题，目前仅对变量数ｎ＜７的线性可分问题给予过讨论。本文基于简化问题讨论和优化问题的解的思想，提出了稳健分类复杂度的概念，并对Ｂｏｏｌｅ函数稳健分类复杂度为１的稳健线性可分问题，提出了对这类Ｂｏｏｌｅ函数进行计数的方法，并给出了计数结果     

THE LINEAR KERNEL OF BOOLEAN FUNCTIONS AND PARTIALLY-BENT FUNCTIONS

1.IntroductionBentFunctionsformaveryimportantclassofbooleanfunctionsincryptographybecauseoftheirperfectnonlinearity,buttheyareneitherbalancednorthefirstordercorrelationimmune,andveryfewofthemareknown.In[1],Carlet,C.gavethedefinitionofPartiallyBentFunction…     

ALL ADMISSIBLE LINEAR ESTIMATES OF REGRESSION COEFFICIENTS UNDER MATRIX LOSS

The necessary and sufficient conditions for a linear estimator of a linear estimable functionof regression coefficients in a general fixed effects linear model with the assumptions of normality to beadmissible in the class of all estimators under matrix liss function are given.For a general randomeffects or mixted effects linear model the necessary and sufficient conditions are obtained too.     

Well-Posedness of Fully Coupled Linear Forward-Backward Stochastic Differential Equations

This paper studies the well-posedness of fully coupled linear forward-backward stochastic differential equations(FBSDEs). The authors introduce two main methods-the method of continuation under monotonicity conditions and the unified approach-to ensure the existence and uniqueness of solutions of fully coupled linear FBSDEs. The authors show that the first method(the method of continuation under monotonicity conditions) can be deduced as a special case of the second method(the unified approach). An example is given to illustrate it in linear FBSDEs case. And then, a linear transformation method in virtue of the non-degeneracy of transformation matrix is introduced for cases that the linear FBSDEs can not be dealt with by the the method of continuation under monotonicity conditions and the unified approach directly. As a powerful supplement to the the method of continuation under monotonicity conditions and the unified approach, linear transformation method overall develops the well-posedness theory of fully coupled linear forward-backward stochastic differential equations which have potential applications in optimal control and partial differential equation theory.     

不确定离散广义时滞系统的静态输出反馈控制

针对一类不确定离散时滞广义系统,给出了静态输出反馈控制器的设计方法.首先基于标称离散广义时滞系统的稳定条件,以受限线性矩阵不等式形式,得到闭环离散广义时滞系统正则、因果且渐近稳定的充分条件,同时利用受限矩阵不等式的可行解给出静态输出反馈控制器的设计方法;然后采用矩阵的正交补,把求受限线性矩阵不等式的可行解问题转化为求严格线性矩阵不等式的可行解;最后的数值实例说明了所给方法的有效性和正确性.     

Global convergent algorithm for the bilevel linear fractional-linear programming based on modified convex simplex method

A global convergent algorithm is proposed to solve bilevel linear fractional-linear programming,which is a special class of bilevel programming.In our algorithm,replacing the lower level problem by its dual gap equaling to zero,the bilevel linear fractional-linear programming is transformed into a traditional single level programming problem,which can be transformed into a series of linear fractional programming problem.Thus,the modified convex simplex method is used to solve the infinite linear fractional programming to obtain the global convergent solution of the original bilevel linear fractional-linear programming.Finally,an example demonstrates the feasibility of the proposed algorithm.     

发酵过程混合神经网络模型及其仿真

提出了一种新型的发酵过程混合神经网络模型，该模型由非线性神经网络和线性神经网络两部分组成，由于非线性神经网络采用结构具有线形式的Flat网络，两个网络能够合并为同一表达式，并具有线性形式，可采用线性最小二乘法求解网络权值，与串联结构及串并联结构混合神经网络模型相比，该模型训练方式简单，并可方便地使用在线辨识算法。     

线性时变RLCM网络瞬态分析的一种新方法

本文从电路理论和数值积分的基本原理出发．导出了线性时变ＬＣＭ的通用伴随模型，提出了线性时变ＲＬＣＭ网络瞬态分析的一种新方法──伴随模型法。采用这种方法，不仅可以使线性时变ＲＬＣＭ网络的瞬态分析变得如同线性时不变电阻性网络的直流分析一样简单，而且很容易满足不同精度要求和数值稳定性的需要。     

一类零售商驱动型供应链契约问题

研究了不同信息结构下零售商驱动型供应链契约问题.对于由1个供应商和1个零售商构成的供应链,考察了线性契约以及2部线性契约.在完全信息及非对称信息两种条件下分别给出了供应商和零售商的最优契约,就批发价格、零售价格及利润进行了比较,并对由供应商、零售商驱动的两种供应链中信息的价值进行了对比研究.理论分析以及数值算例表明,供应商选择2部线性契约优于线性契约,对于完全信息条件,2部线性契约下零售商的期望利润大于线性契约下的期望利润.本文的研究结论对于零售商驱动型供应链的契约设计以及协调问题具有重要意义.     

Generalized <Emphasis Type="Italic">p</Emphasis>-values for testing regression coefficients in partially linear models

The one-sided and two-sided hypotheses about the parametric component in partially linear model are considered in this paper. Generalized p-values are proposed based on fiducial method for testing the two hypotheses at the presence of nonparametric nuisance parameter. Note that the nonparametric component can be approximated by a linear combination of some known functions, thus, the partially linear model can be approximated by a linear model. Thereby, generalized p-values for a linear model are studied first, and then the results are extended to the situation of partially linear model. Small sample frequency properties are analyzed theoretically. Meanwhile, simulations are conducted to assess the finite sample performance of the tests based on the proposed p-values.     

多操纵面交叉耦合的SQP控制分配策略

针对多操纵面飞机交叉耦合效应下易产生虚拟控制误差和舵效中和等问题,提出了一种基于改进序列二次规划的控制分配策略。以操纵面偏量为参数构建优化目标,基于舵效线性假设分别研究了基于线性规划和二次规划的多操纵面线性控制分配方法。进一步考虑非线性交叉耦合效应,分别建立了序列线性和序列二次规划的交叉耦合控制分配模型,并设计了改进的Hessian矩阵,以实现序列二次规划的优化求解。仿真表明,基于改进序列二次规划的控制分配策略能够合理地利用所有交叉耦合操纵面实现非线性分配,优于线性规划、二次规划和序列线性规划控制分配方法。     

Distribution of one-error linear complexity of binary sequences for arbitrary prime period

Complexity measures for sequences,such as the linear complexity and the k-error linear complexity,play an important role in stream ciphers.This contribution studies the distribution of 1-error linear complexity of binary sequences with arbitrary prime period.For any odd prime N,the authors present all possible values of 1-error linear complexity of N-periodic binary sequences,and derive the exact formulas to count the number of N-periodic binary sequences with any given 1-error linear complexity.     

A Parallel Algorithm for Solving Block-diagonal Structured Large Linear System

1　 PrologueWith the speedy development of global science technology,modern society has becomemore systematical and informative in many fields such as engineering technology,socialeconomy,organism and zoology. Many complicated large systems have appeared,as ITtechnology develops like wildfire,it is strongly required to improve scientific and correctdecisions,which makes originally complicated large system become more complex.Practical applications of linear program are getting far-ranging and…     

条件线性高斯模型的Gauss Hermite filter-Kalman filter算法

针对条件线性高斯状态空间模型,提出了高斯厄密特滤波-卡尔曼滤波(Gauss Hermite filter-Kalmanfilter,GHF-KF)滤波算法。算法将模型中的条件线性状态方程代入观测方程,并融合线性状态的过程噪声和观测噪声,由GHF获得非线性状态的估计;再将非线性状态的估计均值代入线性状态方程与观测方程,由KF获得线性状态的估计;获得的非线性状态估计方差还用于修正由KF估计的线性状态,以提高精度。将GHF-KF算法应用于目标跟踪的仿真结果表明,与现有Rao-Blackwellized粒子滤波器RBPF相比,新方法在保证估计精度的同时,明显提高了实时性,计算时间仅约为RBPF的5%。     

线性生成的完全模糊线性微分系统

基于模糊结构元方法, 定义了模糊数和模糊值函数的乘法运算, 研究了由对称模糊结构元线性生成的完全模糊线性微分系统的求解问题, 给出了系统解存在的充要条件, 得到了结构元线性生成的齐次、 非齐次的完全模糊线性微分系统求解方法．同时, 给出了这类模糊线性微分系统在经济、军事领域的实际应用．     

一类线性系统求解的并行算法

本文给出了求解块角结构的大线性系统的一种并行算法 .这一方法以“梯度—单纯形”法为基础 ,将大线性问题分解为若干子线性系统 ,通过并行地对各个子系统求解 ,求得大系统的最优解 .该算法提高了大系统求解速度 ,特别适合于耦合约束较少的大线性问题 .本文还对该算法的应用性进行了分析.