自方幂数问题

本软件主要用于结构的时域试验模态分析，包括单输入单输出，单输入多输出和多输入多输出程序设计。传统的模态分析软件大多是基于频域分析方法，需首先对采样信号进行Fourier 变换。本软件使用实测时域信号，无需Fourier变换，可以避免由于信号截断而引起泄露、出现旁瓣、分辨率低等问题对辨识精度的不利影响。此外，节省了计算机运算时间，可以对实际工况状态下的结构进行在线参数识别。(This software is mainly used for the structure of time-domain experimental modal analysis, including single-input single-output, single-input multiple-output and multiple-input multiple-output programming. Traditional modal analysis software are mostly based on frequency domain analysis, needed first sampled signal Fourier transform. The software uses the measured time-domain signal without the need for Fourier transform, avoid truncated because of the signal caused by leaks, there sidelobes and low resolution of the issue of adverse effects on the identification accuracy. In addition, the savings in computing time, to the actual condition of the structure of the state-line parameter identification.)

这是仿真跳时序列超宽带带的源代码，希望我能给所需的人提供一点帮助。(This is the simulation dancers sequence UWB with the source code, I hope I can provide the necessary assistance.)

剔除数据异常值，这个程序是比较小一点的 (Remove data outliers, this procedure is relatively smaller)

MATLAB的GUI调用进行图像处理 边缘检测(MATLAB GUI call for image processing edge detection)

说明：  处理波形，计算声波再通过障碍物以后的延迟,从而计算声波在不同介质中的传播速度(Treatment of waveform, calculated the time delay after the sound waves pass through the obstaclesand，In order to estimate the acoustic propagation velocity in different media)

本文将SOM（自组织特征映射）和PNN（概率）神经网络应用到柴油机故障诊断中，首先介绍了SOM和PNN神经网络的算法，然后对柴油机的故障进行了分析，并运用matlab进行了仿真，验证了实验结果。(This article will SOM (self-organizing feature map) and PNN (probability) neural network is applied to fault diagnosis of diesel engine, first introduced the SOM and PNN neural network algorithm, and then analyses the fault of diesel engine, and has carried on the simulation using matlab, verify the experimental results.)

说明：  AES加密算法中的S-盒及其MATLAB实现,S盒实现是MATLAB中的主要过程。(AES encryption algorithm in the realization of S-boxes and MATLAB, S box MATLAB implementation is the main process.)

为严格(Exact)径向基网络来实现非线性的函数回归(Strict (Exact) radial basis function network to achieve nonlinear regression)

COntrole de courant avec Modulation Vectorielle

Canny邊緣檢測的函數 a: input image sigma: Gaussian的均方差