Research and Design of Network Management Construction Based on Mobile AGENT

The technical characters of mobile agent （MA） originated in the distributional artificial intelligence domain is introduced. A network management construction based on agent （NMCA） is then proposed. The NMCA structure features are elaborated in detail. A prototype design of NMCA is given by using the jKQML programming. The establishment of NMCA platform will be helpful to reduce the correspondence load of network management and improves the efficiency and the expansion ability of network management systems.     

Iterative regularization methods for atmospheric remote sensing

In this paper we present different inversion algorithms for nonlinear ill-posed problems arising in atmosphere remote sensing. The proposed methods are Landweber's method (LwM), the iteratively regularized Gauss-Newton method, and the conventional and regularizing Levenberg-Marquardt method. In addition, some accelerated LwMs and a technique for smoothing the Levenberg-Marquardt solution are proposed. The numerical performance of the methods is studied by means of simulations. Results are presented for an inverse problem in atmospheric remote sensing, i.e., temperature sounding with an airborne uplooking high-resolution far-infrared spectrometer.     

湖泊藻类叶绿素-α和悬浮物浓度的高光谱定量遥感模型研究

本文利用地物光谱仪对太湖水体进行了光谱测量和同步采样分析，对获得的数据尝试用光谱分离法进行分析，从中分离出蓝藻和悬浮物的特征波峰，建立波峰高度与同步水质采样得到的叶绿素-α浓度和悬浮物浓度的对应关系，得出其遥感定量反演算法，并实际应用在OMIS成像光谱仪图像上．     

斐索梯度折射率光纤透镜传感实验

采用LD泵浦的单纵模Nd：YVO4倍频激光器、梯度折射率光纤透镜等器件构成斐索梯度折射率光纤透镜传感实验仪．本文介绍了实验装置和实验原理，并给出了实验结果。     

基于组织协同进化分类算法的遥感图像目标识别

针对遥感图像目标识别问题,提出了一种基于组织协同进化分类算法的识别方法。它没有复杂的运算,训练和识别速度都很快。对实测遥感图像的实验表明,本文方法性能稳定,优于文献[3]和[4]中基于支撑矢量机的方法,识别率均达到了95％以上,且训练时间非常短,不到1秒钟。     

Level of nodes in increasing trees revisited

Simply generated families of trees are described by the equation T(z) = ϕ(T(z)) for their generating function. If a tree has n nodes, we say that it is increasing if each node has a label ∈ { 1,…,n}, no label occurs twice, and whenever we proceed from the root to a leaf, the labels are increasing. This leads to the concept of simple families of increasing trees. Three such families are especially important: recursive trees, heap ordered trees, and binary increasing trees. They belong to the subclass of very simple families of increasing trees, which can be characterized in 3 different ways. This paper contains results about these families as well as about polynomial families (the function ϕ(u) is just a polynomial). The random variable of interest is the level of the node (labelled) j, in random trees of size n ≥ j. For very simple families, this is independent of n, and the limiting distribution is Gaussian. For polynomial families, we can prove this as well for j,n → ∞ such that n − j is fixed. Additional results are also given. These results follow from the study of certain trivariate generating functions and Hwang's quasi power theorem. They unify and extend earlier results by Devroye, Mahmoud, and others. © 2007 Wiley Periodicals, Inc. Random Struct. Alg., 2007     

一种低频 空间定向及高灵敏遥感方法研究

本文提出一种低频、空间定向及高灵敏的遥感方法。文中介绍了传感器及其二次仪表设计原理和关键技术。由作者研制的本检测系统,在空气中的定向接收灵敏度,离1米处高达120mV/μPa,比HP4905A型机的输出信噪比高8倍.     

A linearized vector radiative transfer model for atmospheric trace gas retrieval

We present a plane parallel radiative transfer model for polarized light, that provides the intensity vector as well as the derivatives of the four Stokes parameters with respect to atmospheric trace gas profiles. These derivatives are essential for retrieval of height resolved trace gas information from satellite measurements of backscattered sunlight. The model uses the Gauss-Seidel iteration technique for solving the radiative transfer equation. For the first time, the forward-adjoint radiative perturbation theory is applied for the linearization of a radiative transfer model including polarization. The accuracy of the model is better than 0.025% for all four Stokes parameters and better than 0.03% for the derivatives.     

Analytic evaluation of the weighting functions for remote sensing of blackbody planetary atmospheres: a general linearization approach

An analytic approach is proposed for the evaluation of weighting functions for remote sensing of a blackbody planetary atmosphere based on straightforward, general linearization. In the present paper, this approach is applied to the case of remote sensing with the nadir (down-looking) geometry. Expressions for weighting functions for various atmospheric parameters are derived. It is demonstrated that in a realistic case of temperature-dependent atmospheric absorption, an additional term appears in the expression for the temperature weighting function which contains the temperature derivative of the atmospheric absorption coefficient. The approach is applied to the case of a semi-infinite atmosphere and then, to the atmosphere of a finite optical depth with the underlying surface. In this, latter case, the expressions are also obtained for partial derivatives of observed radiances with respect to surface parameters: surface pressure, temperature and emissivity.     

利用星载多波长辐射计观测资料反演大气气溶胶光学厚度

本文提出了一个利用星载多波长辐射计的可见光和近红外通道观测资料反演气溶胶光学厚度的迭代方案。数值试验结果表明，该方案反演气溶胶光学厚度的误差小于10％。将该方案用于分析我国东南沿海上空NOAA－AVHRR观测资料，得到了较为合理的气溶胶光学厚度的空间分布。