New design and analysis of finite difference domain decomposition algorithm for the two-dimensional heat equation

<正> It is presented in this paper that the new design and its analysis of finite difference domaindecomposition algorithms for the two-dimensional heat equation,and the numerical results have shownthe stability and accuracy of the algorithms,where Saul'yev asymmetric schemes have been used atthe interface points.The Algorithm Ⅱ in this paper has further extended those developed by Dawsonand the others,Zhang and Shen.     

Integral-type tests for goodness-of-fit

<正> A family of integral-type goodness-of-fit tests is investigated.This family includes someexisting tests,such as the Cramér-von Mises test and Anderson-Darling test,etc.The asymptoticdistributions of the tests in the family under the null and local alternative hypotheses are established.The almost sure convergence under a fixed underlying distribution is obtained.Furthermore,simulationsare conducted to compare the powers of the tests in the family.Simulation results show that fordifferent alternatives,the more powerful tests are different,and the parameter λ has great influence onthe tests in small sample cases.     

Analysis for gene networks based on logic relationships

The reverse construction and analysis of the networks of molecular interactions are essential for understanding their functions within cells. In this paper, a logic network model is constructed to investigate the complicated regulation mechanism of shoot genes of Arabidopsis Thaliana in response to stimuli. The dynamics of the complicated logic network is analyzed, discussed, and simulated. The simulation results show that the logic network of the active genes of shoot eventually evolves into eleven attractors under the stimuli, including five 1-periodic and six 2-periodic attractors. Our work provides valuable reference and guidance for biologists to understand and explain Arabidopsis’ response to external stimuli by experiments.     

A new approach of available transfer capability incorporating wind generation

The approach of available transfer capability (denoted as ATC) incorporating wind generation has been paid very high attention since the development of wind generation. Based on the maximum function, this paper presents an ATC model. The characteristic of the new model is twofold. First, it considers wind turbines connected to power system and static security of power system simultaneously. Second, it is a system of semismooth equations and can be solved easily. By using the smoothing strategy, a smoothing Newton method is adopted for solving the proposed new ATC model. Numerical simulation results of the IEEE 30-bus and 118-bus system show that the new model and algorithm are feasible and effective. The impact of wind turbines connected to power system on ATC is also analyzed.     

DISTRIBUTED FINITE-TIME χ-CONSENSUS ALGORITHMS FOR MULTI-AGENT SYSTEMS WITH VARIABLE COUPLING TOPOLOGY

<正> This paper considers finite-time χ-consensus problem for a multi-agent system with firstorderindividual dynamics and switching interaction topologies.Several distributed finite-time consensusrules are constructed for multi-agent dynamics in a unified way with the help of Lyapunovfunction and graph theory as well as homogeneity.Time-invariant non-smooth forms of finite-timeneighbor-based controllers are proposed and a numerical example is shown for illustration.     

Performance analysis of optimal channel estimation and multiuser detection in a randomly-spread CDMA channel

<正> This paper analyzes performance of optimal channel estimation and multiuser detection(MUD) in a block-fading code-division multiple-access (CDMA) channel on the assumptions of randomspreading and large-system limit,by using the replica method developed in statistical mechanics.The authors find that the asymptotic spectral efficiency of the linear minimum mean-squared error(LMMSE) MUD which was proposed and analyzed by Evans and Tse in 2000 is indistinguishable fromthat of the optimal MUD for small system loads.Our results imply that performance of MUD scarcelyimproves even if one spends more computational cost than that of the LMMSE MUD,i.e.,at most thecube of the number of users,on the above-described conditions.     

Adaptive tracking control for actuator failure compensation based on MT-filters

<正> This paper considers the problem of actuator failure compensation for a class of nonlinearsystems in the form of output-feedback.MT-filters are exploited to estimate the unmeasured states.The backsteppping technique is used to construct the controller recursively.The proposed compensationscheme can grantee the boundedness of all the closed-loop signals and asymptotic output tracking.Thetheoretical results are illustrated by a simulation example.     

Boundary control of two PDE’s separated by interface conditions

<正> This paper discusses the null boundary controllability of two PDE's,modeling a compositesolid with different physical properties in each layer.Interface conditions are imposed.     

A line search filter secant method for nonlinear equality constrained optimization

<正> This paper formulates and analyzes a line search method for general nonlinear equalityconstrained optimization based on filter methods for step acceptance and secant methods for searchdirection.The feature of the new algorithm is that the secant algorithm is used to produce a searchdirection,a backtracking line search procedure is used to generate step size,some filtered rules areused to determine step acceptance,second order correction technique is used to reduce infeasibility andovercome the Maratos effect.Global convergence properties of this method are analyzed:under mildassumptions it is showed that every limit point of the sequence of iterates generated by the algorithmis feasible,and that there exists at least one limit point that is a stationary point for the problem.Moreover,it is also established that the Maratos effect can be overcome in our new approach by addingsecond order correction steps so that fast local superlinear convergence to a second order sufficient localsolution is achieved.Finally,the results of numerical experiments are reported to show the effectivenessof the line search filter secant method.     

基于岭回归径向基神经网络的MIMU误差建模

对MEMS（Micro Electro Mechanical systems微电子机械系统）IMU（Inertial Measurement Unit惯性测量单元）的随机漂移和误差进行建模和补偿是提高捷联惯导系统性能的主要方法之一。为了避免径向基（RBF）神经网络输出之间可能存在的复共线性,更加准确有效的对MIMU的输出误差建模,提出将岭回归径向基神经网络用于MIMU的误差建模中。通过与时间序列建模方法的仿真比较表明,在对MIMU误差补偿上所建立的岭回归RBF网络与四阶AR模型方法精度相当,比一阶AR模型精度高,而且无需对数据平稳性处理。

Abstract：

It is one of the main methods to improve the performance of Strap-down Inertial Navigation System for compensating the random drift and bias of MEMS （Micro Electro Mechanical systems） IMU （Inertial Measurement Unit）. In order to eliminate latent multicollinearity of radial basis function neuron network output layer and model the drift and bias of MIMU accurately,the radial basis function neuron network based on ridge regression method was proposed which was applied in modeling and compensating MIMU errors. The simulation shows,compared to the AR model,the precision of compensation of MIMU error using radial basis function neuron network based on ridge regression method is equal to the fourth order AR model,better than first order AR model,and no data stabilization processing.