The Design of Discrimination Experiments

Experimentation plays a fundamental role in scientific discovery. Scientists experiment to gather data, investigate phenomena, measure quantities, and test theories. In this article, we address the problem of designing experiments to discriminate between two completing theories. Given an initial situation for which the two theories make the same prediction, the experiment design problem is to determine how to modify the situation such that the two theories make different predictions for the modified situation. The modified situation is called a discrimination experiment. We present a knowledge-intensive method called DEED for designing discrimination experiments. The method analyzes the differences in the two theories' explanations of the prediction for the initial situation. Based on this analysis, it determines modifications to the initial situation that will result in a discrimination experiment. We illustrate the method with the design of experiments to discriminate between several pairs of qualitative theories in the fluids domain.     

Generalization of the Gram-Charlier/Edgeworth Series and Application to Time-Frequency Analysis

We derive a general equation relating probability densities and as special cases we the obtain Gram-Charlier and Edgeworth series. This allows us to generalize these methods and clarify a number of issues pertaining to both probability theory and time-frequency analysis. In particular we show how the Gram-Charlier and Edgeworth series are related to the kernel method of time-frequency analysis. The approach allows us to construct densities that satisfy given constraints such as joint moments or conditional moments. Also, we show that the kernel has to be signal dependent and that to obtain a proper distribution it should be the ratio of two characteristic functions.     

应用图论及广义简约梯度法进行压力管网优化设计

广义简约梯度法(GRG)是非线性规划算法中最有效的算法之一，本文把图论应用于广义简约梯度法优化的过程中，使输入简便，计算简化，应用GRG算法对武汉市的汉阳管网进行了模拟优化设计，并对管段的计算管径用线性规划法进行标准化，取得了满意的结果     

Neural networks,rational functions,and realization theory

The problem of parametrizing single hidden layer scalar neural networks with continuous activation functions is investigated. A connection is drawn between realization theory for linear dynamical systems, rational functions, and neural networks that appears to be new. A result of this connection is a general parametrization of such neural networks in terms of strictly proper rational functions. Some existence and uniqueness results are derived. Jordan decompositions are developed, which show how the general form can be expressed in terms of a sum of canonical second order sections. The parametrization may be useful for studying learning algorithms.This work was supported by the Australian Research Council, the Australian Telecommunications and Electronics Research Board, and the Boeing Commencai Aircraft Company (thanks to John Moore).     

不完全信息下的最终报价仲裁

基于争议双地仲裁人的裁决值有不同的概率估计，而这些估计是双方共同知识这一前提分析最终报价中仲裁，把它构造成一个不完全信息的非零和对策模型。然后给出了局部、全局Ｎａｓｈ平衡报价策略存在唯一的充分条件，最后探讨了双方认识存在的差异对争议人报价行为的影响。     

非线性隔振理论初探

本文以线必阻尼，立方刚度非线性系统为例，对非线性隔振理论进行了初步探讨，导出了系统的无量纲运动响应和传递率，并与线性隔振系统进行了比较，着重讨论了非线性对它们的影响，获得了一些有用的结论。     

高速微粒携基因侵入植物细胞的速度条件

本文围绕基因枪技术中用高速微粒向植物细胞中导入外源基因的速度条件，分析了其中的三个动力学过程：发射宏弹、加速微弹、侵入细胞．提出了气动撞击发射式基因枪中弹簧刚度应满足的条件；得到了一种用理论分析与试验测试相结合确定微弹出射速度的方法；找到了微弹侵入植物细胞的最小速度条件。从而为基因枪的设计提供了理论依据。     

混凝土受拉断裂的破坏机理

本文从试验现象出发,建立了以数理统计为基础的混凝土受拉全过程曲线方程。研究表明,混凝土受拉应力应变全曲线是混凝土试件内部的粘结界面与水泥胶合物在外拉力作用下逐步断裂造成的。文章所建立的方法不仅可以解释许多试验现象,模拟混凝土受拉全曲线,而且还可以得出试验中难以测出的结果。     

Pi-coefficient analysis of update algorithms for adaptive systems

This paper finds the appropriate pi-coefficients for a parameter estimation adaptive system and uses them to analyze the stability of two estimation algorithms. The estimation error dynamics of the system are modeled by a linear time-invariant subsystem and a nonlinear time-varying update law in a feedback loop. Then the so-called max-p problems are formulated and solved to obtain the pi-coefficients for the linear subsystem and nonlinear update low. For the investigated system, the quantitative results show that the least-squares update algorithm has larger stability range than that of the gradient algorithm, and the σ-modification scheme gives larger stability ranges for both algorithms.