MVM

this is a pdf that the prof give to studnts

里面有很多图像边缘检测的算法，可以从提供的网站上下载图片进行操作(There are many edge detection algorithms that can be downloaded from the website to provide pictures to operate)

这种方法一方面将像素的灰度值分散，可以分辨图象中比较细节的内容；另一方面，将图 象的灰度变化控制在一定范围之内，抑制了噪声的产生，较大程度上地保留了原始图象的亮度．(This approach on the one hand spread the pixel gray value, the more details you can identify the contents of the image the other hand, the image gray scale control in a certain range, suppress noise generation, a greater degree preserved on the original image brightness.)

this is a MPSK mudulation with BER and PSD .

说明：  MATLAB的经典书籍，moler编写的MATLAB和实验应用(MATLAB' s classic books, moler applications written in MATLAB and experimental)

svm matlab标准模板，共初学者使用

step models for switch tactile

温度PID控制功能块FB58使用入门 西门子自适应 以及C语言源代码(PID temperature control function block FB58 Getting Started Siemens adaptive and C language source code)

说明：  针对低信噪比环境下基于能零比的端点检测方法准确率低的问题,提出了一种结合谱减法和短时零熵法的端点检测方法。首先通过功率谱减法对带噪语音进行降噪处理,然后结合短时平均过零率特征与谱熵特征,构造出一种新的语音参数,即短时零熵,最后运用双门限算法进行端点检测。实验结果表明该方法在复杂噪声环境下具有良好的端点检测性能,降低了检测的误判率。(To solve the problem of low accuracy of endpoint detection method based on energy zero ratio in low SNR environment, an endpoint detection method combining spectral subtraction and Short-term zero entropy method is proposed. Firstly, the noise is reduced by power spectrum subtraction, then a new speech parameter, short-time zero entropy, is constructed by combining the short-time average zero crossing rate and spectral entropy. Finally, the double threshold algorithm is used for endpoint detection. The experimental results show that this method has good performance of endpoint detection in complex noise environment, and reduces the rate of detection error.)

迭代法是解线性代数方程组的另一类方法，特别适用于解大型稀疏线性方程组。它的基本思想是针对求解问题预先设计好某种迭代格式，从而产生求解问题的近似解迭代序列，在迭代序列收敛于精确解的情况下，按精度要求取某个迭代值作为问题解的近似值。迭代法具有原始系数举证始终不变，算法简单，编写程序较方便，所需存储单元较少的优点。(iterative method was the linear algebraic equations of the other methods, particularly applicable to the large sparse linear equations. The basic idea is to solve the problem in advance against the design iteration some good format, thereby creating problems for the approximate solution of iterative sequence, the iterative sequence converges to the exact solution, precision demanded by a certain value as a question iterative solution approximation. Iteration with the original proof coefficient remains unchanged, the algorithm is simple, the preparation process more convenient, less required storage unit advantages.)