Lévy processes and Fourier multipliers

We study Fourier multipliers which result from modulating jumps of Lévy processes. Using the theory of martingale transforms we prove that these operators are bounded in Lp(Rd) for 1<p<∞ and we obtain the same explicit bound for their norm as the one known for the second order Riesz transforms.     

Moments of claims in a Markovian environment

This paper considers discounted aggregate claims when the claim rates and sizes fluctuate according to the state of the risk business. We provide a system of differential equations for the Laplace–Stieltjes transform of the distribution of discounted aggregate claims under this assumption. Using the differential equations, we present the first two moments of discounted aggregate claims in a Markovian environment. We also derive simple expressions for the moments of discounted aggregate claims when the Markovian environment has two states. Numerical examples are illustrated when the claim sizes are specified.     

WAVELET TRANSFORM IN FRACTAL IMAGE ENCODING

This paper presents some results of the relation between wavelet transform and fractal transform. The wavelet transform of the attractor of fractal transform posseses translational and scale invariance. So we speed the fractal image encoding by testing the invariance of the wavelet transform appropriate for image encoding. The classfication scheme of range blocks by wavelet transform is given in this paper.     

Hereditary optimal control problems: Numerical method based upon a padé approximation

In this paper, we consider a particular approximation scheme which can be used to solve hereditary optimal control problems. These problems are characterized by variables with a time-delayed argumentx(t – ). In our approximation scheme, we first replace the variable with an augmented statey(t) x(t - ). The two-sided Laplace transform ofy(t) is a product of the Laplace transform ofx(t) and an exponential factor. This factor is approximated by a first-order Padé approximation, and a differential relation fory(t) can be found. The transformed problem, without any time-delayed argument, can then be solved using a gradient algorithm in the usual way. Four problems are solved to illustrate the validity and usefulness of this technique.This research was supported in part by the National Aeronautics and Space Administration under NASA Grant NCC-2-106.     

高分辨阿达玛变换显微荧光图像分析(Ⅱ)单细胞DNA荧光图像生成、处理及自动定量分析研究

本研究把荧光显微镜，阿达玛变换多通道成像技术和计算机图象处理技术结合起来，建立了一种单细胞DNA荧光图像自动定量分析系统，对系统的成像原理、信号编码和解码方法及单细胞定量分析方法进行了讨论，分析结果表明，本系统提供的单细胞定量分析数据稳定可靠。     

傅里叶变换技术在紫外可见光谱区的应用

本文评述了傅里叶变换在紫外可见光谱区的应用，探讨了傅里叶变换在紫外可见光谱学以及信号处理两方面的内容。详细介绍了傅里叶变换在紫外可见区遇到的问题、主要优点和发展前景。     

FTS-20E富里叶红外光谱仪数据系统改造

报道了ＦＴＳ－２０Ｆ富里叶红外光谱仪数据系统改造的工作采用ＩＢＭ４８６计算机及新的数据接口取代了陈旧的ＮＯＶＡ４数据系统，文章详细描述了其硬件设计和软件编辑，改造不仅更新了ＦＴＳ－２０Ｅ里叶红外光谱仪，而且还使其达到９０年代的水平。     

红外镜反射光谱的测试与解析

红外镜反射（infrared specular reflection，简称SR）光谱与被测样品和衬底的折射指数、吸收指数以及入射角有密切关系，往往由之产生畸变。要从红外镜反射技术测得的光谱处理得到人们熟悉的吸收光谱，需要经过较复杂的计算机数学处理。本文通过几个比较特殊的镜反射例子，以说明镜反射光谱的测试和解析必须注意多种影响因素。     

原位漫反射红外光谱研究氮氧化物在Ag-ZSM-5催化剂上的吸附态及选择性催化还原反应机理

利用原位分析方法对催化剂表面吸附态进行动态表征，对了解催化反应机理具有重要的意义。漫反射红外光谱是一种理想的原位方法，应用该方法在298－773K范围原位考察了以丙烯为还原剂，NO在Ag-ZSM-5催化剂上的吸附态及选择性催化还原过程。认为NO的选择性催化还原符合直接作用机理，还原的关键是形成有机－氮氧化物（R－NO2或R－ONO）中间体。O2的作用是使C3H6充分活化，并是有效产生有机－氮氧化物不可缺少的条件。     

Multivariate calibration of near infrared spectra by orthogonal WAVElet correction using a genetic algorithm

Orthogonal WAVElet correction (OWAVEC) is a pre-processing method aimed at simultaneously accomplishing two essential needs in multivariate calibration, signal correction and data compression, by combining the application of an orthogonal signal correction algorithm to remove information unrelated to a certain response with the great potential that wavelet analysis has shown for signal processing. In the previous version of the OWAVEC method, once the wavelet coefficients matrix had been computed from NIR spectra and deflated from irrelevant information in the orthogonalization step, effective data compression was achieved by selecting those largest correlation/variance wavelet coefficients serving as the basis for the development of a reliable regression model. This paper presents an evolution of the OWAVEC method, maintaining the first two stages in its application procedure (wavelet signal decomposition and direct orthogonalization) intact but incorporating genetic algorithms as a wavelet coefficients selection method to perform data compression and to improve the quality of the regression models developed later. Several specific applications dealing with diverse NIR regression problems are analyzed to evaluate the actual performance of the new OWAVEC method. Results provided by OWAVEC are also compared with those obtained with original data and with other orthogonal signal correction methods.