ldpc_code

赫尔辛基科技大学有关于盲信号去噪的的matlab工具箱，非常好用。希望对大家有用(about the denoise matlab blind source separation from hitu。it is very cool got it!)

MATLAB是目前国际上被广泛接受和使用的科学与工程计算软件。(MATLAB is widely accepted internationally and use scientific and engineering calculation software.)

This routine draws a circle with center defined as X_CENTER,,Y_CENTER, radius as a scaler RADIUS.

基于严格波耦合分析的matlab软件，可分析体相位光栅的衍射效率(The diffraction efficiency of volume phase grating can be analyzed based on the MATLAB software.)

用ｍａｔｌａｂ实现的遗传算法，包括遗传算法中的交叉，选择，变异操作，适合初步了解遗传算法( realize the genetic algorithm　ｗith MATLAB, including the cross, the genetic algorithm selection, mutation operation, suitable for a preliminary understanding of the genetic algorithm)

matlab sourcecodes documents

雷达数据处理对于观测的目标位置数据（称为点迹）进行滤波处理，自动形成航迹，并且可以对下一个目标的位置进行估计预测。利用最小二乘算法（LMS）进行滤波处理，得到了比较稳定的航迹估计。 最小二乘方法是参数估计中一种较为常见的参数估计方法。对于雷达观测数据，在我们假定已经精确知道航迹的运动学模型之后，通过建立观测方程，即可以对于模型的参数，如初速度，初始位置和加速度等进行最小均方误差估计。采用序贯最小二乘的方法可以对观测数据进行实时处理，已对待估计参数进行实时更新，然后利用观测模型可以对 数据进行滤波计算。(Radar data processing for target position data observed (known as trace points) filter processing, automatic track, and can be estimated to predict the position of the next target. Using the least squares algorithm (LMS) filtering process, have been relatively stable track estimates. Least-squares parameter estimation method is a more common parameter estimation method. For radar data, we assume that the kinematic model has been accurately track after, through the establishment of observation equations, which can be the parameters of the model, as ever speed, acceleration, etc. initial position and minimum mean square error estimation. Sequential least squares method using the observed data can be processed in real time, has been to treat the estimated parameters are updated in real time, and then use observational data can be filtered model calculations.)

说明：  维纳率波器的仿真研究，一个做圆周运动的物体，经观测后有一定的误差和噪声影响，经维纳滤波后轨迹更加清(Wiener rate of wave device simulation, a circular motion of the object to do by observing the error and after some noise by Wiener filtering path is more clear)

斯坦福大学关于非线性问题的求解，nonlinear problems (nonlinear problems)

关于压缩感知中算法重构做得仿真，供参考。(Compressed sensing reconstruction algorithm for the simulation done for reference.)