时滞种群模型的正周期解对所有正解的吸引性

建立了对数种群模型Ｎ′（ｔ）＝Ｎ（ｔ）｛ｒ（ｔ）－ａ１（ｔ）ｌｎ［Ｎ（ｔ）］－ａ２（ｔ）ｌｎ［Ｎ（ｔ－τ（ｔ））］｝的周期正解的存在性，并得到了正周期解对所有正解的吸引性．     

压差式矢量水听器方位估计中的干扰抵消

矢量水听器由于能获取声场中标量（声压）和矢量（振速）信息，因此单个的矢量水听器就可实现目标方位估计。单个矢量水听器是利用信号的声压和质点振速之间相关性进行信号方位估计，但是当存在干扰，并且干扰和信号之间相关时，如果对运用能量流进行方位估计的方法不加改进，则会出现很大的误差，甚至出现错误的估计。本文提出一种存在已知噪声干扰情况下的干扰抵消方法，并针对该方法进行了仿真试验，最后运用湖试数据进行了验证。结果表明，该方法能有效地减弱相千千柑对信号的影响，实现对信号的方位估计。     

Pattern时延差编码四信道水声通信技术研究

本文所研究的是基于Pattern时延差编码（PDS）体制下的水声通信技术.PDS水声编码体制利用Pattern码片出现在码元窗的时延差值进行时延编码,通过码元分割,有效的降低了水声信道的多途干扰;通过频率分割划分四个通信信道,增加通信速率至1000bit/s.在接收端利用带通滤波器来实现通信信道分割,每个信道再应用拷贝相关器实现码元分割并估计出时延差值,完成译码.仿真实验表明,该系统适合于大量不同水声信道高可靠性工作,为水声通信网络化打下坚实基础.     

Stein's idea and minimax admissible estimation of a multivariate normal mean

We consider estimation of a multivariate normal mean vector under sum of squared error loss.We propose a new class of minimax admissible estimator which are generalized Bayes with respect to a prior distribution which is a mixture of a point prior at the origin and a continuous hierarchical type prior. We also study conditions under which these generalized Bayes minimax estimators improve on the James–Stein estimator and on the positive-part James–Stein estimator.     

计算金属间化合物热力学性质的新方法

用一简单的相关函数式对金属间化合物的热力学性质进行拟合，提出了一种计算金属间化合物热力学性质的新方法，并用此方法计算了二元金属间化合物的常温热容和熵。计算结果表明，该方法简单，且能满足一定的计算精度，有一定的实用价值。     

Simple correction for perturbations of peak amplitudes in statistical models of overlap

Summary The application of statistical models of overlap (SMOs) to saturated separations is made possible by theory that addresses variable peak amplitudes. These amplitudes cause peak widths to vary, and this variation can be modeled by a random variable whose effect on the probability of overlap is expressed by a convolution integral. Modified probabilities of overlap are derived for both homogeneous and nonhomogeneous one-dimensional separations, and the new probabilities are compared to results determined from published computer simulations. The new theory can describe overlap at saturations that are 3 to 4 times larger than before. Previously reported experimental chromatograms are reinterpreted to show the capabilities of theory. The theoretical extension is an important step towards making SMOs into practical tools for screening analytical separations.     

Initial data truncation for multivariate output of discrete-event simulations using the Kalman filter

Data truncation is a commonly accepted method of dealing with initialization bias in discrete-event simulation. An algorithm for determining the appropriate initial-data truncation point for multivariate output is proposed. The technique entails averaging across independent replications and estimating a steady-state output model in a state-space framework. A Bayesian technique called Multiple Model Adaptive Estimation (MMAE) is applied to compute a time varying estimate of the output's steady-state mean vector. This MMAE implementation features the use, in paralle, of a bank of Kalman filters. Each filter is constructed under a different assumption concerning the output's steady-state mean vector. One of the filters assumes that the steady-state mean vector is accurately reflected by an estimate, called the assumed steady-state mean vector, taken from the last half of the simulation data. As the filters process the output through the effective transient, this particular filter becomes more likely (in a Bayesian sense) to be the best filter to represent the data and the MMAE mean estimator is influenced increasingly towards the assumed steady-state mean vector. The estimated truncation point is selected when a norm of the MMAE mean vector estimate is within a small tolerance of the assumed steady-state mean vector. A Monte Carlo analysis using data from simulations of open and closed queueing models is used to evaluate the technique. The evaluation criteria include the ability to construct accurate and reliable confidence regions for the mean response vector based on the truncated sequences.     

Volumetric properties of the boldine + alcohol mixtures at atmospheric pressure from 283.15 to 333.15 K: A new method for the determination of the density of pure boldine

Densities of boldine + alcohol binary mixtures were measured over the whole accessible range of boldine compositions at temperatures from 283.15 to 333.15 K using an Anton-Paar digital vibrating glass tube densimeter. The binary systems studied include, as a solvent, seven normal alcohols from n-C₁ to n-C₆, n-C₈, and isopropanol. The density of these systems has been found an increasing function of the boldine composition. A new methodology based on density data of solutions of solid solutes with normal alcohols is described in order to determine solid molar volume of pure solutes. This methodology was validated with pure solid naphthalene molar volumes data at 298.15 K, with an average uncertainty of 6%.     

On Estimation of Temperature Uncertainty Using the Second Order Adjoint Problem

The uncertainty of temperature prediction from the heat flux error is estimated using first and second order adjoint equations. The adjoint codes developed for the inverse heat transfer problems provide the uncertainty estimation for the corresponding forward problems. Numerical tests corroborate the feasibility of fast uncertainty estimation using Hessian maximum eigenvalue obtained via second order adjoint equations.