M

这是数字信号处理的算法和综合和优化电子书，是全英文的，解压密码压缩包中有。(This is a digital signal processing algorithm and the synthesis and optimization of e-books, are all in English, extracting passwords are compressed.)

Moment s Hu algorithm

OTSU Gray-level image segmentation using Otsu s method. Iseg = OTSU(I,n) computes a segmented image (Iseg) containing n classes by means of Otsu s n-thresholding method (Otsu N, A Threshold Selection Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern. 9:62-66 1979). Thresholds are computed to maximize a separability criterion of the resultant classes in gray levels. OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the corresponding Iseg is therefore a binary image. The pixel values for Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ... [Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability criterion within the range [0 1]. Zero is obtained only with images having less than n gray level, whereas one (optimal value) is obtained only with n-valued images.

说明：  matlab实现陷波器，采用的是LMS 算法实现，能将特定的正弦信号滤去(matlab notch filter realization using the LMS algorithm, the sinusoidal signal to a particular least squares)

流行学习isomap（有标注，便于更好理解等距映射方法在高维数据降维过程的实现）(Popular learning isomap (have annotations, facilitate better understanding isometric mapping method in the implementation of the high-dimensional data dimension reduction))

三相电压型 ＰＷ Ｍ 整流器，三相电压型 ＰＷ Ｍ 整流器，三相电压型 ＰＷ Ｍ 整流器(Three-phase voltage type PWM rectifie)

基于levelset的测地活动轮廓 matlab源码，可实现多目标轮廓的 提取。对噪声图象具有良好的鲁棒性。但是计算量较大，耗时过多(levelset based on the geodesic active contour Matlab source, more achievable goal contour extraction. Image noise is a good robust. However, the large amount of calculation, time-consuming excessive)

Matleb的学习课件，适合初学者学习使用。(Matleb learning courseware, suitable for beginners learning to use.)

彩色图转灰度图++matlab+实现代码，很不错，值得看看！(Color to grayscale++matlab+ implementation code, very good, worth a look!)

This program contains the explicit descriptions of load forecasting by the Mathworks web site and is very complete. the users can easily apply their own data to it and use the methods to forecast Load and price.