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传号、空号差分码的simulink模拟产生程序(Mark, simulink simulation empty number Differential Code Generator)

说明：  基于粒子群优化的无线MESH网信道分配算法通用MATLAB函.源码由GreenSim团队原创(PSO-based wireless MESH network channel allocation algorithm for general MATLAB function. GreenSim team from the original source)

different classifier for matlab

Useful tool for rendering and outputting information rich images(This function can be used in place of IMAGE, IMAGESC and IMSHOW, but does so much more. It is fast and displays images as they should be- correct aspect ratio, integer magnification, no axes. In addition, it can return the image as an output variable- useful for saving to disk, texture mapping surfaces, and post-rendering manipulation such as overlaying/combining two or more images. All the MATLAB built-in colormaps are implemented, but without MATLAB s nasty discretization artifacts. Plus, there are many new colormaps which are helpful for viewing more complex data, such as optic flow, likelihoods over images, difference images, segmentations, stereo image pairs (as anaglyphs) and edge-maps with orientation. It also accepts user defined linear and non-linear colormaps.)

A coursework that i do in my digital Communication to calculate mean height

transformateur power system

说明：  一种FxLMS自适应滤波算法 LMS自适应滤波算法RLS自适应滤波算法变换域自适应滤波算法仿射投影算法共扼梯度算法基于子带分解的自适应滤波算法基于QR分解的自适应滤波算法算法性能评价变步长的自适应滤波算法时变系统跟踪速度与收敛精度方面对算法调整步长因子u的矛盾,但变步长中的其它参数的选取还需实验来确定,应用起来不太方便。对RLS算法的各种改进,其目的均是保留RLS算法收敛速度快的特点而降低其计算复杂性。变换域类算法亦是想通过作某些正交变换使输入信号自相关矩阵的特征值发散程度变小,提高收敛速度。而仿射投影算法的性能介于LMS算法和RLS算法之间。共扼梯度自适应滤波算法的提出是为了降低RLS类算法的复杂性和克服某些快速RLS算法存在的数值稳定性问题。信号的子带分解能降低输入信号的自相关矩阵的特征值发散程度,从而加快自适应滤波算法的收敛速度,同时便于并行处理,带来了一定的灵活性。(A FXLMS adaptive filtering algorithm)

说明：  所传为共轭梯度法和线性加权法，这两种方法在优化中有较大的作用！(The transfer to the conjugate gradient method and linear weighted method, the two methods in optimization have a greater role!)

基于均匀线阵、一个信号源的music算法程序，希望对初学music算法的同学有帮助吧！(Music algorithm based on uniform linear array, a signal source procedure, the beginner students of the music algorithm it!)

实现信号的稀疏分解，基本的分解，优化为互相关，再优化为fft(Realization of signal sparse decomposition, basic decomposition, optimization of cross-correlation, optimization for FFT)