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雷达信号处理中的一个重要过程：利用匹配滤波中的相关原理，对目标进行定位(Radar signal processing, an important process: the use of matched filtering principle to locate the target)

The Weather Radar Product Synthetic Programming by VC++ & MATLAB.pdf

Algorithm of the decision of a problem of distribution of heat in a pipe a method of final differences

DFT进行频谱分析时的三种现象 1、混叠：对连续信号采样，要求连续信号是带限的，采样频率要足够高。Fs应满足Nyquist采样定理才不产生混叠。 采样前加低通滤波器防混叠 2、频谱泄漏：DFT对时域信号进行了截断（相当于采样信号乘了一个窗函数），时域的乘积相当于频域卷积，改变了原信号频谱。 改用其他窗函数（非矩形）改善泄漏。 3、栅栏现象：DFT 只给出了频谱在采样点上的取值，采样点间的频谱内容丢失。(DFT spectrum analysis of a three phenomena, aliasing : continuous signal sampling, requiring continuous signal is band-limited, the sampling frequency should be high enough. Fs meet the Nyquist Sampling Theorem would not have aliasing. Sampling former low-pass filter plus anti-aliasing 2, spectrum leakage : DFT right time domain signal a disconnect (equivalent to a sampling signal by a window function). time domain is equivalent to the product of frequency-domain convolution, changes in the spectrum of the original signal. Window functions to switch to other (non-rectangular) to improve leakage. 3, fenced phenomenon : DFT spectrum is given only at the sampling point value, sampling points of the spectrum as lost.)

通过恢复低秩矩阵得到显著性图，其中详细的运用了mean-shift算法，可以很好的了解mean-shift算法的使用，同时还包含了RPCA算法。(Significantly through the recovery of low rank matrix diagram, which detailed the use of mean-shift algorithm, can be a very good understanding of the use of the mean-shift algorithm, also contains RPCA algorithm.)

基于Hessian能量的半监督回归，并将其应用于半监督维数约简。(This is code for the semi-supervised regression using Hessian energy. Kwang In Kim, Florian Steinke and Matthias Hein, "Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction" NIPS 2009)

image rotate using hough transform to detect the edge of image.

一种分割细胞的方法，利用matlab进行的图像处理程序(A segmentation method of cells, using matlab for image processing)

STBLERND generates random numbers form the Levy alpha-stable distribution

naive bayes分类法的matlab实现，包含训练和测试部分(naive bayes classification matlab realize, including training and testing parts)