薛定谔方程快速傅里叶算法 NLSE 3D map

惯性导航仿真，matlab，很好的仿真程序。(inertial simulation in Matlab)

余弦变换压缩，用于图像压缩，压缩比高，且压缩后图像质量仍然很好。适用于灰度图象。(Cosine Transform compression for image compression, compression ratio, and compressed image quality is still good. Apply to the gray-scale image.)

code source matlab segmentation

svm程序，下载后可以直接运行，但需要结合data数据。没有密码(svm program can be run directly after download, but requires a combination of data data. No password)

在非线性光纤光学的必须仿真方程，包括spm，xpm以及损耗的薛定谔方程。其中有10多个小仿真程序，以及其中用到的函数。(Must the simulation equation in nonlinear fiber optics, including the SPM, XPM and depletion of the schrodinger equation.There are more than 10 small simulation program, and the use of the function.)

完成智能天线的T程序仿真，通过仿真可以输出天线的MUSIC算法的结果(Smart antenna to complete the T process simulation, simulation can be output through the antenna of the results of the MUSIC algorithm)

说明：  矩形阵波束形成代码，快速高效的算法，，经典波束形成算法(Rectangular array beamforming code, fast and efficient algorithm, the classical beamforming)

黄锷论文中EMD和HHT的源程序，已经打包压缩,解压后可以使用(Wong Ngok paper on EMD and HHT source, has been packaged compression, decompression can be used after)

标准压缩感知（CS）理论决定了可靠的信号恢复是可能给M= O（KLOG（N / K））的测量。我们证明了它可以通过利用超越简单的稀疏性和可压缩性由包括价值观和信号系数的位置之间的依赖关系更加逼真信号模型大大降低Mwithout牺牲的鲁棒性。(The standard compressive sensing (CS) theory dictates that robust signal recovery is  possible from  M=O(Klog(N/K))  measurements. We demonstrate that it is possible to substantially  decrease  Mwithout sacrificing robustness by leveraging more  realistic signal models that go beyond simple sparsity and  compressibility by including dependencies between values and  locations of the signal coefficients.   )

SIFT -MATCH BY David Lowe USING C AND MATLAB(SIFT-MATCH BY David Lowe USING C AND MATLAB)