theinterp

一个不错的图像质量评价测度实现，用于泛型图像质量评价，需要参照图像。内有相关文献名称。(a good measure to evaluate image quality achieved for the Generic Image quality evaluation, needs light images. Have names related literature.)

Matlab simulation of Fiber dispersion

contains reeedsolomon code for wireless complete systm

可以进行概率计算，也可以进行取余运算，可以实现图像的基本操作(Probability can be calculated, but also can take over operations, the basic operation of the image can be achieved)

Voice activity detection Using low band to full band energy ratio

digital image processing about filters

这是一个简单的FFT为无电位1 +1 +1 Ð 薛定谔方程的光束传播方法。如果该软件灵活，允许引入的术语（如果是极少数需要包括色散效应高阶导数）。例如，如果一个人渴望解决的一个方程的形式： （四/ dz的+ Ð ^ 2/dx ^ 2 - 0.25 * Ð ^ 3/dx ^ 3）== 0 Ÿ 它可以解决使用以下代码： Ž = linspace（0,1,512） x = linspace（-5,5,1024） psi0 =进出口（- x的。^ 2） Ð = D_lateral1D（十，2）-0.25 * D_lateral1D（十，3） 字段= LinearBPM（psi0，有D，Z） 凡D_lateral1D是一个函数，提供“取代”的微分算子。 这个函数是在一个非线性的BPM，我曾对（分步，谱方法等），将提交给我，当我完成他们的文件和组织功能更复杂的设置非常初期阶段。 (This is a simple FFT based beam propagation method for potential-free 1+1+1D Schrodinger equation. The software if flexible and allows to introduce high-order derivatives in the term (very handful if is needed to include dispersion effects). For example, if one desires to solve an equation in the form: (d/dz+ d^2/dx^2- 0.25*d^3/dx^3)Y == 0 It can be solved using the following code: z=linspace(0,1,512) x=linspace(-5,5,1024) psi0=exp(-x.^2) D=D_lateral1D(x,2)-0.25*D_lateral1D(x,3) field=LinearBPM(psi0,D,z) Where D_lateral1D is a provided function that "replaces" the derivative operator. This function is a very early stage in a more complex set of non-linear BPM functions that I have made (split-step, spectral methods, etc.) and I will submit them when I finish their documentation and organization. Sorry for my English, I m eager for your comments. )

用互信息作为两幅图像的相似性度量进行配准(Using mutual information as the two images of the similarity measure for registration)

使用带通滤波器对图像进行处理，其中daitongfilter。m是带通滤波器函数(The use of band-pass filter for image processing, which daitongfilter. m is the band-pass filter function)

这是一篇关于高斯伪谱法的源代码，具有很好的指导意义(This is a Gaussian pseudo-spectral method on the source code, with a good guide)