An-Introduction-to-Programming-and-Numerical-Meth

说明：  通信仿真及实例详解。对matlab学习者很有帮助啊(communications simulation and example explanation. Right Matlab learners helpful ah!)

无刷直流电机simulink仿真模型,搭建的simulink模型(wu sha dian ji)

混频向量自回归模型，用于处理混频数据，可以避免同频数据导致的信息缺失(mixfrequency VAR)

利用大津算法对焊点图像进行分割，去除多余噪声(Solder joint image segmentation using Otsu algorithm to remove the excess noise)

模糊聚类的matlab工具箱。。。内含说明文档(Fuzzy clustering matlab toolbox. . . Includes documentation)

用MATLAB编写的有限元程序，包含了有限元求解的各个细节过程。(MATLAB prepared by the finite element program, including the finite element solution details.)

this matlab program show the ROC ie. reciver operating characterstics. it shows how to plot ROC in matlab . the example is taken from Maurad Barkat- Artech publication

Canny edge detector algorithm matlab codes This part gives the algorithm of Canny edge detector. The outputs are six subfigures shown in the same figure: • Subfigure 1: The initial "lena" • Subfigure 2: Edge detection along X-axis direction • Subfigure 3: Edge detection along Y-axis direction • Subfigure 4: The Norm of the image gradient • Subfigure 5: The Norm of the gradient after thresholding • Subfigure 6: The edges detected by thinning

小波变换及编码在图像图形处理中有着重要的应用，本压缩包属于小波编码及其演示的matlab库函数，希望对大家的学习有帮助。(Wavelet transform and image coding has important applications in graphics processing, the wavelet encoding and compression packages are demo matlab library function, we hope to help learning.)

Advances in data collection and storage capabilities during the past decades have led to an information overload in most sciences. Researchers working in domains as diverse as engineering, astronomy, biology, remote sensing, economics, and consumer transactions, face larger and larger observations and simulations on a daily basis. Such datasets, in contrast with smaller, more traditional datasets that have been studied extensively in the past, present new challenges in data analysis. Traditional statistical methods break down partly because of the increase in the number of observations, but mostly because of the increase in the number of variables associated with each observation. The dimension of the data is the number of variables that are measured on each observation.