pattern

优秀论文及配套源码。Hilbert-Huang变换(HHT)是一种新的非平稳信号处理技术，该方法由经验模态 分解(EMD)与Hilbert谱分析两部分组成。任意的非平稳信号首先经过EMD方法处理后被分解为一系列具有不同特征尺度的数据序列，每一个序列称为一个固有模态函数(IMF)，然后对每个IMF分量进行Hilbert谱分析得到相应分量的Hilbert谱，汇总所有Hilbert谱就得到了原信号的谱图。该方法从本质上讲是对非平稳信号进行平稳化处理，将信号中真实存在的不同尺度波动或趋势逐级分解出来，最终用瞬时频率和能量来表征原信号的频率含量。 本文研究了基于HHT的暂态电能质量扰动检测方法，介绍了HHT的基本原理和利用HHT检测电能质量多扰动信号的实现方法。仿真试验表明该方法可以实时检测扰动的起止时刻，持续时间和扰动幅度，适用于电能质量多扰动的监测和辨识系统。 (Hilbert-Huang Transform(HHT) is a new non-stationary signal processing technology，including the Empirical Mode Decomposition(EMD) and Hilbert spectral analysis．In this method，arbitrary non-stationary signals was divided into a series data sequence with different characteristic scales after the first EMD treatment，each sequence is called an intrinsic mode function(IMF)，and then each IMF component gained corresponding the Hilbert spectrum though Hilbert spectrum analysis，a summary of all Hilbert spectrum assembled to the spectra of the original signal．In essence，this method is a stable processing for non-stationary signal，which decomposed the different fluctuations or trends in the signal in rum，and represented the frequency content of the original signal using the final instantaneous frequency and energy． This paper study a method to detect power quality disturbances based on the HHT，in which the principle and the realization of the HHT and the realization of power quality disturbance)

一个2D的FDTD模拟算例，包括完整的定义、初始化、更新方程、显示和FDTD迭代文件。该算例适合初学FDTD的人员掌握完整流程。(A 2D FDTD simulation examples, including a complete definition, initialization, update equations, display and FDTD iteration file. This example is suitable for beginners FDTD personnel to master the complete process.)

基于谷歌地球平台的matlab程序开发，方便我们使用。(matlab programming Based on Google earth platform, which is convenient for us to use.)

说明：  综合评价与决策方法，同样是与数学建模有关的内容。(Evaluation and decision making, and mathematical modeling is also related to the content.)

BPSK SEL分集程序，仿真了分集带来的性能增益(SEL diversity gains)

说明：  薛定宇教授编写的分数阶工具箱，适合新手入门(Professor xue dingyu prepared the fractional level toolbox)

说明：  MATLAB进行有限元分析时应用该用限元工具箱，很好用的(MATLAB finite element analysis application of the Limited yuan toolbox, with the good)

time-invariant degradation models and stationary signals and noise, the classical Fourier domain Wiener filter, which can be implemented in O(N logN) time, gives the minimum mean-square-error estimate of the original undistorted signal. For time-varying degradations and nonstationary processes, however, the optimal linear estimate requires O(N2) time for implementation. We consider filtering in fractional Fourier domains, which enables significant reduction of the error compared with ordinary Fourier domain filtering for certain types of degradation and noise (especially of chirped nature), while requiring only O(N logN) implementation time. Thus, improved performance is achieved at no additional cost. Expressions for the optimal filter functions in fractional domains are derived, and several illustrative examples are given in which significant reduction of the error (by a factor of 50) is obtained.

说明：  计算序列x=[3 0 2 1 3 4 6] 和y=[3 0 -2 1 -3]的线性卷积(Calculation sequence x = [3 0 2 1 3 4 6] and y = [3 0-2 1-3] the linear convolution)

Clear Case briefly introduction power point