OFDM_rece_matlab

Transmission line fault detection and classification

dds信号发生器，matlab7.0，dspbuilder7.0(dds signal generator, matlab7.0, dspbuilder7.0)

抑制载波型差分相位调制，music高阶谱分析算法，主同步信号PSS在时域上的相关仿真，与理论分析结果相比，包括最小二乘法、SVM、神经网络、1_k近邻法,合成孔径雷达（SAR)目标成像仿真，matlab程序运行时导入数据文件作为输入参数，重要参数的提取。( Suppressed carrier type differential phase modulation, music higher order spectral analysis algorithm, PSS primary synchronization signal in the time domain simulation related, Compared with the results of theoretical analysis, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Synthetic Aperture Radar (SAR) imaging simulation target, Import data files as input parameters matlab program is running, Extract important parameters.)

时兴的前推回代算法程序，可用于求解辐射状配电网三相潮流。(Forward-Backward Sweep algorithm for three-phase load-flow analysis of radial distribution systems.)

Exact Recovery of Sparsely-Used Dictionaries

We address the problem of blind carrier frequency-offset (CFO) estimation in quadrature amplitude modulation, phase-shift keying, and pulse amplitude modulation communications systems.We study the performance of a standard CFO estimate, which consists of first raising the received signal to the Mth power, where M is an integer depending on the type and size of the symbol constellation, and then applying the nonlinear least squares (NLLS) estimation approach. At low signal-to noise ratio (SNR), the NLLS method fails to provide an accurate CFO estimate because of the presence of outliers. In this letter, we derive an approximate closed-form expression for the outlier probability. This enables us to predict the mean-square error (MSE) on CFO estimation for all SNR values. For a given SNR, the new results also give insight into the minimum number of samples required in the CFO estimation procedure, in order to ensure that the MSE on estimation is not significantly affected by the outliers.

end point detection is an matlab program for voice processing

OFDM调制 16QAM.包含星座图，相位，载波等。(16qam ofdm)

数据挖掘的作业，基于DBSCAN的分类，数据集为iris，可以学习下(Data mining, classification based on DBSCAN, the data set is iris, you can learn under )

矢量化编程技巧,基本的一些调试技巧，适合于初学者，非常有用(failed to translate)