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codage programmes pour la parole

精通MATLAB参考源码第10章，喜欢MATLAB和神经网络的可以好好学习下，绝对的好资源！(Chapter X proficient MATLAB reference source, like MATLAB and neural networks can learn, the absolute good resource! )

matlab,数字图像处理技术，关于图像的边缘检测(matlab, digital image processing technology, on the edge of the image detection)

用节点导纳矩阵计算三相短路电流。输入数据-形成节点阻抗矩阵-选择故障点-计算短路电流-计算个节点电压-计算指定支路的电流(this procedure is used node admittance matrix calculation of three-phase short-circuit current input data-- forming node impedance matrix-- election Optional fault-calculation of short-circuit current-voltage computing nodes designated calculated slip road-- Electricity)

编写M文件，创建如下图形窗口，分别绘制如下图所示的曲线。 （1）曲线y=sin(t)sin(9t)，要求采用红色，点线。横坐标取值范围[0~ ]，标注x轴、y轴并加标题。 （2）一组余弦曲线，其振幅分别为0.4，0.6和0.8。横坐标取值范围[0~2 ]。添加图例与标题。进入图形编辑状态，调整图例的位置。 （3）分别绘制peaks函数的曲面图和网格线图。对曲面图做平滑处理，并添加标题与colorbar。 (Write M file, create the following graphics window, curves were plotted as shown below. (A) the curve y = sin (t) sin (9t), require the use of a red dotted line. The abscissa in the range [0 ~  ], labeled x-axis, y-axis and a title. (2) a set of a cosine curve, and the amplitude was 0.4, 0.6, 0.8. Abscissa value range [0 ~ 2  ]. Add a legend and title. Into the graphical editing mode, adjust the position of the legend. (3) were drawn surface chart peaks function and grid line graph. Surface charts do for smoothing and add titles and colorbar.)

说明：  cca典型相关分析的多变量版本mcca，典型的一种盲源分离算法(Multivariate version of canonical correlation analysis)

说明：  紧支撑小波基构造课程资料 以构造紧支撑正交db小波为例(wavelet)

光伏电池的MATLAB仿真建模 提供多参数修改的用户界面 包括温度 光照强度等参数对电池模块的影响(MATLAB simulation of photovoltaic cells to provide multi-parameter model to modify the user interface, including light intensity, temperature and other parameters of the battery module)

MATLAB結合HTK的特徵擷取應用SVM函式 的實際範例 並且可達到即時錄音辨識 輸出 前三個語音辨識的機率 (MATLAB with HTK feature extraction practical examples of application of SVM function and can reach the probability of the first three speech recognition in the real-time recording identification output)

说明：  image segmentation using matlab