Existence results for second order boundary value problem of impulsive dynamic equations on time scales

In this paper, Schaefer's fixed point theorem and nonlinear alternative of Leray-Schauder type are used to investigate the existence of solutions for second order boundary value problem for impulsive dynamic equations on time scales.     

An existence theorem for neutral variational problems of Bolza

This note proves an existence theorem for a generalized Bolza-type problem that has time delays in both the state and velocity variables. The assumptions are stated in terms of a modification of the classical Hamiltonian, and extend ideas of Rockafellar to the delay case.     

抛物型时滞偏微分方程解振动的充要条件

讨论一类多滞量抛物型时滞偏微分方程解的振动性质，获得了其一切解振动的充要条件及一些充分条件；指出了其与普通抛物型偏微分方程解的质的差异．     

Sequential Estimation of the Parameters in a Trigonometric Regression Model with the Gaussian Coloured Noise

This paper considers the estimation problem for a trigonometric regression model with the noise specified by the Ornstein–Uhlenbeck process with unknown parameter. We propose a sequential procedure which ensures a prescribed mean square precision uniformly in the nuisance parameter. The asymptotic behaviour of the procedure duration mean has been studied. This revised version was published online in August 2006 with corrections to the Cover Date.     

Regression quantiles for unstable autoregressive models

This paper investigates regression quantiles (RQ) for unstable autoregressive models. The uniform Bahadur representation of the RQ process is obtained. The joint asymptotic distribution of the RQ process is derived in a unified manner for all types of characteristic roots on or outside the unit circle. It involves stochastic integrals in terms of a sequence of independent and identically distributed multivariate Brownian motions with correlated components. The related L-estimator is also discussed. The asymptotic distributions of the RQ and the L-estimator corresponding to the nonstationary componentwise arguments can be transformed into a function of a normal random variable and a sequence of i.i.d. univariate Brownian motions. This is different from the analysis based on the LSE in the literature. As an auxiliary theorem, a weak convergence of a randomly weighted residual empirical process to the stochastic integral of a Kiefer process is established. The results obtained in this paper provide an asymptotic theory for nonstationary time series processes, which can be used to construct robust unit root tests.     

On locating low altitude moving targets using a planar acoustic sensor array

It is of engineering importance to locate low altitude moving targets with acoustic methods due to the blindness of the traditional radar detecting. In this paper, an algorithm for locating low altitude moving targets is put forward based on a five-element planar acoustic sensor array. The method is realized through estimations of the sensor-to-sensor time delays of the source signal generated by the low altitude moving target. The angle and range estimation performance of the proposed method are analyzed, respectively, both in theoretical and numerical sense.     

Nonparametric estimation of distributions with categorical and continuous data

In this paper we consider the problem of estimating an unknown joint distribution which is defined over mixed discrete and continuous variables. A nonparametric kernel approach is proposed with smoothing parameters obtained from the cross-validated minimization of the estimator's integrated squared error. We derive the rate of convergence of the cross-validated smoothing parameters to their ‘benchmark’ optimal values, and we also establish the asymptotic normality of the resulting nonparametric kernel density estimator. Monte Carlo simulations illustrate that the proposed estimator performs substantially better than the conventional nonparametric frequency estimator in a range of settings. The simulations also demonstrate that the proposed approach does not suffer from known limitations of the likelihood cross-validation method which breaks down with commonly used kernels when the continuous variables are drawn from fat-tailed distributions. An empirical application demonstrates that the proposed method can yield superior predictions relative to commonly used parametric models.     

高阶非线性波动方程的有限差分方法

本文研究一类广泛的高阶非线性波动方程组初边值问题的有限差分格式，用离散泛函分析方法和先验估计的技巧得到了有限差分格式的收敛性。     

无失效数据的Bayes和多层Bayes分析

本文推广了文献[6]的结果，对指数分布无失效数据的失效率，给出了Bayes估计、Bayes置信上限以及多层Bayes估计，从而可以得到无失效数据可靠度的估计，最后，结合实际问题进行了计算。