ip_tables

说明：  数字图像处理 小波处理 ，去噪音，比基于傅里叶变换的去噪方法好。 含噪信号经过预处理，然后利用小波变换把信号分解到各尺度中，在每一尺度下把属于噪声的小波系数去掉，保留并增强属于信号的小波系数，最后再经过小波逆变换恢复检测信号。(The noisy signal is pre-processed, then the signal is decomposed into different scales by wavelet transform. The wavelet coefficients belonging to noise are removed at each scale, and the wavelet coefficients belonging to the signal are retained and enhanced. Finally, the detected signal is restored by inverse wavelet transform. It is better than the denoising method based on Fourier transform.)

基于背景减除的单目标跟踪方法在Matlab中的实现，包含测试用avi文件(Background subtraction based on a single-target tracking method in Matlab, implementation, including test avi file)

Image to be embedded into an image

自己画的一条简单的Bezier曲线，通过四个控制点（控制点可自行选取）(She painted a simple Bezier curve through four control points (control points can be selected as their own))

压缩感知中经典的匹配追踪算法，稀疏变换包含小波基和离散余弦变换基。(The classical matching pursuit algorithm in compressed sensing includes sparse wavelet transform and discrete cosine transform base.)

说明：  平滑滤波，空域滤波与变换域滤波比较，从中说明其中原理(The principle of smoothing filtering is explained by comparing spatial filtering with transform domain filtering)

说明：  利用matlab所编程的许多例子，帮组大家学习matlab(Matlab programming by using many examples to help everyone learn matlab Group)

先用PCA降维，在利用支持向量机进行分类，这个分类是二分类，所以PCA的降维降到两维即可分类。(Firstly, PCA dimensionality reduction is used to conduct classification with support vector machine. This classification is binary classification, so the dimensionality reduction of PCA can be reduced to two dimensions for classification.)

多层mie散射程序,可以模拟多层粒子的散射情况。(multi-layer mie scatter )

说明：  基于角谱理论艾里光束的传播,该MATLAB程序，大体上模拟出了Airy光束的二维光强分布，并在此基础上利用角谱理论，编写出了其在二维平面内的传播，只需改变其中的参数就可以展示Airy光束的移动。在此基础上加上障碍物，可以得到Airy光束的自愈合特性等特殊性质(The matlab program, in general, simulates the two-dimensional light intensity distribution of Airy beam, and on this basis, using the angle spectrum theory, compiles its propagation in the two-dimensional plane, only changing the parameters can show the movement of Airy beam. On this basis, the self-healing properties of Airy beams can be obtained by adding obstacles)