Fundamentals_of_Statistical_Signal_Processing-Esti

小波变换有关突变点的检测，通过离散小波变换与连续小波变换进行对比(Wavelet transform on the detection of mutations, through the discrete wavelet transform are compared with the continuous wavelet transform)

Calculate displacement and strain a series of images

运用FDTD算法计算了喇叭天线的近场分布，有一定的参考价值。(Use the FDTD algorithm to calculate the the horn antenna near-field distribution, there is a certain reference value.)

CharArrayWriter extends Writer Source Code for Andriod.

海杂波服从K杂波，K杂波在matlab中的实现(The sea clutter obey K Clutter, Clutter K implementation in matlab)

matlab7.0的ppt教材，教授一些基本且常用的命令，帮助初学者掌握matlab的使用。(matlab7.0 the ppt textbooks, professors, some of the basic and commonly used commands, helping beginners to master the use of matlab.)

生物图像处理 滤波处理 还原 matlab代码(Biological filtering process to restore the image processing matlab code)

k-d树的matlab程序，包含了KDTREE, KDTREEIDX and KDRANGEQUERY functions。提供了两个Demo scripts(kdtree_demo.m & kdrange_demo.m),很实用( This distribution contains the KDTREE, KDTREEIDX and KDRANGEQUERY functions. Included are the source code files in kdtree/src, as well as precompiled mex files for the following systems: - Mac OS X (Matlab 6.5) - Redhat Linux (Matlab 6.5) - Windows (Matlab 6.1) Two demo scripts are provided (kdtree_demo.m & kdrange_demo.m). The new features added June 2004: + You can now use N dimensional data points, where N>3. + Use KDTREEIND to return the index value to the closest point, instead of the closest point values. + KDRANGEQUERY can now return these index values as well. Written by/send comments or suggestions to : Guy Shechter guy at jhu dot edu June 2004 )

模型是结构体类型的线性投影Y = linproj(X, model) 其中W.model为线性投影矩阵， Y = model.W *X + model.b b为偏差值( Description: Y = linproj(X, model) linearly projects data in X such that Y = model.W *X+ model.b out_data = linproj(in_data, model) projects in_data.X out_data.X = model.W *in_data.X+ model.b out_data.y = in_data.y Input: model [struct] linear projection: .W [dim x ncomp] Projection matrix. .b [ncomp x 1] Bias.)

用MATLAB运行主成分，可以求出特征向量，等非常实用。(MATLAB operation principal component, can work out characteristic vector, and very practical. )