LDPC_distribution_under_BEC

很多经典电子电路仿真 仿真工具multism(A lot of classic simulation tools for electronic circuit simulation multism)

极大似然估计是概率论中的重要思想，阅读此文献可以帮助我们了解极大似然估计的含义(Maximum likelihood estimation is important in probability theory thinking, reading this literature can help us understand the meaning of maximum likelihood estimation)

optical loss measurements

matlab挠曲线，剪力图，弯矩图绘制，运行时直接打开boom2.m(matlab deflection curve)

分类工具包，含有多个分类算法的matlab源程序，适用于类别数据的分类和可视化(The Classification toolbox for MATLAB is a collection of MATLAB modules for calculating classification (supervised pattern recognition) multivariate models: Discriminant Analysis, Partial Least Square Discriminant Analysis (PLSDA), Classification trees (CART), K-Nearest Neighbors (kNN) and Soft Independent Modeling of Class Analogy (SIMCA). This is the version 3.1 of the Classification toolbox for MATLAB Classification toolbox for MATLAB has been released by Milano Chemometrics and QSAR research Group. Visit our website at www.disat.unimib.it/chm )

说明：  可以方便地进行1,2范数的优化计算。具体针对稀疏恢复问题，最小二乘问题，约束优化问题的求解等。(It is convenient to optimize the calculation of 1,2 norms. Specifically for sparse recovery problem, least squares problem, constrained optimization problem and so on.)

此程序用于在GUI界面下计算光流，对于研究流的学者有重要参考价值..(this code demenstrates the computation of optical flow.)

粒子群优化算法，优化处理，matlab代码，学习必看(Particle swarm optimization, optimization of processing, matlab code, learning must-see)

完整的MFCC程序，利用MATLAB编写，可直接使用移植使用(Complete MFCC procedure, the use of MATLAB can be used directly transplanted to use)

这是关于RADRA仿真的.有如下代码placeClutter.m, plotDistLines.m, plotFOV.m, radarSimulation.m, runRadarSim.m, targetsReturn.m, radarSimulation.fig, analyzBuffer.m, buildAntenaGain.m, createTargets.m, displayTargets.m, handleRadarControlls.m, MTIcalcTargetsV.m(RADRA simulation. PlaceClutter.m following code, plotDistLines.m, plotFOV.m. radarSimulation.m, runRadarSim.m. targetsReturn.m, radarSimulation.fig. analyzBuffer.m, buildAntenaGain.m. createTargets.m, displayTargets.m. handleRadarControlls.m, MTIcalcTargetsV.m)