红外目标精跟踪方法的研究

本文提出了一种直接把红外前视传感器的输出作为测量值来跟踪红外目标的扩展型卡尔曼滤波跟踪算法。在滤波处理时,设置可变的测量矩阵,其目的在于提高运算速度和抑制噪声干扰。通过具体的实例,对所提跟踪算法的特点和有效性进行了细致的分析。     

WKB近似下的Fourier衍射成象方法

对于介质目标微波衍射成象，本文引入了ＷＫＢ近似来模拟目标内部总场。基于这种近似，我们导出了Ｆｏｕｒｉｅｒ衍射公式，并采用了广义滤波逆传播方法由目标空间谱实现目标特性的重建。计算机模拟结果表明采用ＷＫＢ近似重建目标特性较Ｂｏｒｎ近似有明显改善。     

广义集值强非线性拟变分不等式

本文引入并研究一类新的广义集值强非线性拟变分不等式,讨论这类广义集值强非线性拟变分不等式解的存在性以及由算法所构造的迭代序列的收敛性.我们的结果改进和发展了Noor,Siddiqi和Ansari等人近期的一些主要结果.     

神经网络法计算镉（Ⅱ）,羟基及碳酸根三元体系的形态分布

采用前馈线笥网络ＢＰ算法，计算了Ｃｄ６２＋－ＯＨ＾－ＣＯ＾２－３三元体系的累积稳定常数。用Ｈｏｐｆｉｅｌｄ反馈网络研究了体系中络合物的形态分布。溶液中溶解的ＣＯ２对ｌｇβ１的计算结果有重要影响，对ｌｇβ２，ｌｇβ３，ｌｇβ４的结果影响不大。     

Compact Matrix Expressions for Generalized Wald Tests of Equality of Moment Vectors

Asymptotic chi-squared test statistics for testing the equality of moment vectors are developed. The test statistics proposed are generalized Wald test statistics that specialize for different settings by inserting an appropriate asymptotic variance matrix of sample moments. Scaled test statistics are also considered for dealing with nonstandard conditions. The specialization will be carried out for testing the equality of multinomial populations, and the equality of variance and correlation matrices for both normal and nonnormal data. When testing the equality of correlation matrices, a scaled version of the normal theory chi-squared statistic is proven to be an asymptotically exact chi-squared statistic in the case of elliptical data.     

LZW压缩算法解析及应用设计

ＬＺＷ压缩算法是一种无限压缩算法，它主要是用一种代码来表示数据流中出现的重复串，以达到压缩的目的。     

Max—min神经网络的一种有效学习算法

本文在Ａ．Ｂｌａｎｃｏ等人的算法的基础上，提出了ｍａｘ－ｍｉｎ神经网络的一种改进了的反馈学习算法，严格证明了该算法的迭代收敛性，理论分析及实例计算结果均表明，本文算法具有算法简单，收敛速度快，输出误差小等显著特点。     

广播发射集散控制系统

本文介绍了广播发射台利用计算机技术、网络技术、遥控遥测技术、现代测试手段，对设备进行自动化控制与管理；实现设备技术指标自动测试，发射台无人值班、有人留守，建立机器的计算机档案制度，确保安全优质播出的方法和经验。     

一种遗传-梯度混合算法

本文提出一种函数全局优化的遗传-梯度混合算法。该算法由选择、交叉和诱导变异算子组成。通过对自适应滤波和前向神经网络权值训练两个典型问题的数字仿真，表明该算法是一种快速有效的全局优化算法。     

Assessing the Error Probability of the Model Selection Test

The asymptotic error probability of Linhart's model selection test isevaluated, and compared with the nominal significance level. We examine thecase where the expected discrepancies of the candidate models from the truemodel are asymptotically equal. The local alternatives method is employed inthe limiting operation of the asymptotic evaluation. Although the errorprobability under the null hypothesis is actually shown to be equal to orless than the level for most situations, intolerable violations of the errorcontrol are observed for nested models: It is often erroneously concludedthat the smaller model is significantly better than the larger model. Toprevent this violation, a modification of Linhart's test statistic isproposed. The effectiveness of the proposed test is confirmed throughtheoretical analysis and numerical simulations.