QPSK

模拟2个独立窄带信号分别以20°，60°的方向入射到均匀线阵上，信号间互不相关，与噪声相互独立，噪声为理想高斯白噪声，阵元数为10，快拍数为200，信噪比为20dB，阵元间距分别为 tambada/6 tambada/2、tambada。(Simulate two independent narrowband signals in the direction of 20 °, 60 ° of the incident on the ULA, among signal unrelated, independent noise, the noise is ideal Gaussian white noise, the array element number 10, the number of snapshots for 200, SNR is 20dB, respectively array element spacing  tambada/6 tambada/2, tambada.)

人脸识别 2DMSD 二维最大散度差判别分析 (face recognition 2_dimension scatter difference )

地质统计学中——实验变差函数的计算，对于空间分析很有帮助！(The experiment becomes poor function of computation)

说明：  这是《matlab小波分析》第四章例子的源代码！(This is the &quot matlab wavelet analysis,&quot Chapter IV of the source code examples!)

提出了一种基于小波变换和模糊集的图像融合算法.其基本思想是: 首先对图像进行小波变换,获得图 像的低频和高频分量 随后在融合过程中, 对低频和高频分量采取不同的融合策略, 即对低频分量采用平均能 量法进行融合,对高频成分利用图像的模糊集, 寻求一个模糊隶属函数作为融合算子进行融合 最后再对融合 后的图像进行小波反变换,重构出融合后的图像.实验结果证明了方法的有效性.(Proposed image fusion algorithm based on wavelet transform and fuzzy sets. The basic idea is: First the image wavelet transform to obtain the low and high frequency components of the image followed by low and high frequency components in the fusion process to take a different the integration of strategy, integration of the low frequency components using the average energy method, the use of high frequency components of the image fuzzy sets, look for a fuzzy membership function as a fusion operator for fusion image fusion wavelet transform and re- structure of fused images. experimental results demonstrate the effectiveness of the method.)

This code is for face recognition using PCA

MATLAB中调用Wrapper.cpp的程序的应用 (MATLAB, the application of the procedure call Wrapper.cpp)

MATLAB环境下的直接法 间接法和welch法源程序和谱密度函数的曲线比较(MATLAB environment direct and indirect source Welch law and spectral density function of the curve)

Recent work by Petricoin and Liotta and co-workers (Petricoin et al. Use of proteomic patterns in serum to identify ovarian cancer. Lancet. 2002 Feb 16 359(9306):572-7. PMID: 11867112) has generated a lot of excitement and controversy. This example shows some ways that MATLAB can be used to read, visualize, pre-process (base-line correction, resample) and classify the data. The data can be downloaded from http://home.ccr.cancer.gov/ncifdaproteomics/ppatterns.asp (Recent work by Petricoin and Liotta and co-workers (Petricoin et al. Use of proteomic patterns in serum to identify ovarian cancer. Lancet. 2002 Feb 16 359 (9306) :572-7. PMID: 11867112) has generated a lot of excitement and controversy. This example shows some ways that MATLAB can be used to read, visualize, pre-process (base-line correction, resample) and classify the data. The data can be downloaded from http://home.ccr.cancer. gov/ncifdaproteomics/ppatterns.asp)

matlab 中 svpwm 的算法程序，很好用的(algorithm matlab program in svpwm, well used)