bp9

基于相位的模板匹配算法，此算法快速，可行性较好~(Template matching algorithm based on phase, this algorithm is fast, the feasibility of better ~)

两篇关于运动模糊参数估计和复原的文章，非常经典的文章，基本概括了参数估计的主流方法，(two paper about restore Motion blur,which is very comprehensive )

说明：  一个用matlab编写的地震测井工具集，很实用(Matlab write an earthquake with a set of logging tools, it is practical)

C4.5的matlab实现，并且进行了详细的注释，并进行了有序化处理(C4.5 matlab realize, and conducted a detailed notes, and conducted an orderly processing)

基于chebyshev的水声信号分析，使用拉亚普诺夫指数的公式，是路径规划的实用方法。( Based chebyshev underwater acoustic signal analysis, Raya Punuo Fu index using the formula, Is a practical method of path planning.)

将压缩感知用于谱估计中，根据论文谱压缩感知的一些程序(Compressive sensing (CS) is a new approach to simultaneous sensing and compression of sparse and compressible signals based on randomized dimensionality reduction. To recover a signal from its compressive measurements, standard CS algorithms seek the sparsest signal in some discrete basis or frame that agrees with the measurements. A great many applications feature smooth or modulated signals that are frequency sparse and can be modeled as a superposition of a small number of sinusoids. Unfortunately, such signals are only sparse in the discrete Fourier transform (DFT) domain when the sinusoid frequencies live precisely at the center of the DFT bins. When this is not the case, CS recovery performance degrades significantly. In this paper, we introduce a suite of spectral CS (SCS) recovery algorithms for arbitrary frequency sparse signals. The key ingredients are an over-sampled DFT frame, a signal model that inhibits closely spaced sinusoids, and classical sinusoid parameter e)

Diffusion k-tensor Estimation from Q-ball imaging using discretized principal axes

kalman滤波算法。通过卡尔曼滤波算法，实现对发放信号的滤波还原。(the algorithm of kalman filtering)

说明：  人眼提取，并使用libsvm进行睁闭分类的训练和测试(Position the area of eyes.Train and test the state of eyes by libsvm.)

给出了一个在matlab gui设计中显示图像后无法响应鼠标事件的简单的解决办法 方便易用(Gives the design a matlab gui display images can not respond to mouse events after the simple solution easy to use)