DSE_drone4

基于matlab环境下fisher分布算法的实现，利用矩向量法得到的(Matlab environment based on fisher distribution algorithm, obtained by using moment vector)

matlab voicebox工具箱 函数比较全 matlab voicebox toolbox function more and more to the point of total sub-Bar Moderator(matlab voicebox toolbox function compares the matlab voicebox toolbox function more and more to the point of total sub-Bar Moderator)

用m序列过低通滤波器模拟产生带限高斯白噪声，m序列的长度足够长时功率谱特性接近高斯白噪声的特性。(M-sequence low-pass filter with analog band-limited white Gaussian noise generated, m length of the sequence is long enough the power spectral characteristics close to Gaussian white noise characteristics.)

提出了一种多迸制频移键控(M娲K)信号调制分类及解调方法，选取截获接收机输出的MFSK信 号的时频脊线作为分类特征，利用无监督聚类算法求取最佳聚类数M．利用时频脊线的Ham：小波变换 估计码元宽度，并且利用对应最佳聚类数的聚类中心确定抽判门限，通过对时频脊线抽样判决，实现了 MFSK信号的解调．理论分析和对实际信号的处理结果证明了此算法的可行性．(new algorithm is proposed for elassillcation and demodulation of MFSK signals．The ridge of time— frequency representation of MFSK signals is analyzed．Modulation elassi_fieation is realized by using the unsupervised clustering algorithm to determine the optimal nulnllt2r of clusters．In order to demodulate MFSK signals，the Haar wavelet transform is used to estimate the code—width and the centers of optimal clusters are used to determine thresholds．Theoretical analysis and practical signal processing results justify the robusticity and the efficiency of the new classification and demodulation Mgorithm．)

matlab数字图象处理 matlab数字图象处理 (Matlab digital image processing digital image processing Matlab Matlab digital image processing)

This program is for image segmentation using Expectation maximum

采用MATLAB语言编译的数值积分函数，希望对大家有用(numerical integration)

In statistics, an expectation-maximization (EM) algorithm is a method for finding maximum likelihood or maximum a posteriori (MAP) estimates of parameters in statistical models, where the model depends on unobserved latent variables. EM is an iterative method which alternates between performing an expectation (E) step, which computes the expectation of the log-likelihood evaluated using the current estimate for the latent variables, and a maximization (M) step, which computes parameters maximizing the expected log-likelihood found on the E step. These parameter-estimates are then used to determine the distribution of the latent variables in the next E step.

说明：  关于高阶统计量下的盲均衡算法的一个详细的理论介绍(Order statistics on the blind equalization algorithms under a detailed theoretical description)

说明：  精度测试时延，基于原始套接字，高精度的测量，大学实验用很好(Socket)