基于模糊神经网络的目标识别

提出了一种用于常规雷达目标识别的模糊神经网络．先将目标回波用树状小波变换进行特征抽取，然后用该网络进行识别．最后，给出了５类空中目标的识别实验结果     

电动机的改型设计

在不增加成本的基础上，通过电磁方案的调整，使旧电动机的性能达到新的技术要求     

利用GPS技术进行滩涂测量的新方法

提出了使用GPS技术进行滩涂测量的新方法，并介绍了GPS技术和利用GPS技术进行滩涂测量的方法和技术问题，对效益问题做了讨论。     

Optical dual self functions

A recipe to construct the exact dual self-Fourier-Fresnel-transform functions is shown, where the Dirac comb function and transformable even periodic function are used. The mathematical proof and examples are given Then this kind of self-transform function is extended to the feasible optical dual self-transform functions.     

一阶线性随机系统解过程的小波特性

研究了一阶线性随机系统小波变换的一些性质,得到了一些新结果。     

连续小波变换在机械故障定位检测中的应用

本文从实用角度介绍连续小波变换的主要特性。实例表明在故障定位检测中，其性能优于谱分析，ＡＲ（Ｐ）建模及匹配滤波。     

Numerical inversion of multidimensional Laplace transforms by the Laguerre method

Numerical transform inversion can be useful to solve stochastic models arising in the performance evaluation of telecommunications and computer systems. We contribute to this technique in this paper by extending our recently developed variant of the Laguerre method for numerically inverting Laplace transforms to multidimensional Laplace transforms. An important application of multidimensional inversion is to calculate time-dependent performance measures of stochastic systems. Key features of our new algorithm are: (1) an efficient FFT-based extension of our previously developed variant of the Fourierseries method to calculate the coefficients of the multidimensional Laguerre generating function, and (2) systematic methods for scaling to accelerate convergence of infinite series, using Wynn's ε-algorithm and exploiting geometric decay rates of Laguerre coefficients. These features greatly speed up the algorithm while controlling errors. We illustrate the effectiveness of our algorithm through numerical examples. For many problems, hundreds of function evaluations can be computed in just a few seconds.     

Philippe Flajolet's Research in Analysis of Algorithms and Combinatorics

Philippe Flajolet's research in theoretical computer science spans over more than 20 years. He made lasting contributions to the analysis of algorithms and analytic combinatorics. Among many of his results we mention here some in such diversified topics as enumeration, number theory, formal languages, continued fractions, automatic analysis of algorithms, Mellin transform, digital sums, recurrences, trees, random generation of combinatorial objects, random graphs and mappings, polynomial factorization, communications, codes, graphics, etc. This gives only a small snapshot of his work, and we encourage the reader to visit Flajolet's homepage http://www-rocq.inria.fr/algo/flajolet/index.html for a fuller account. The bibliography was taken from his homepage and may not be totally complete, although we added a few items. Our paper was written without giving any prior notice to Philippe Flajolet. It reflects the view of the authors and any misunderstandings and shortcomings should be put on their account.     

用改进的前向神经网络实现离散Hough变换

介绍了用前向单层神经网络实现离散Ｈｏｕｇｈ变换（ＨＴ）的方法，并且通过对其权值矩阵的修正以及神经元输出函数的修正，改善了ＨＴ的性能，提高了ＨＴ的分辨率。     

基于自校验和互校验的多传感器故障诊断􀀁

本文在系统研究多传感器组中各种故障情况的基础上，将离散子波变换、自校验和互校验技术应用到故障诊断中，提出了包括定理１在内的一些新算法，拓展了故障诊断技术的思路，在生产实践中有着广泛的应用前景。