ACO_on_JSSP

说明：  基于内点法的解l2_l1和l2_TV优化问题的matlab代码(Interior point method based on the solution l2_l1 and optimization problems l2_TV code matlab)

this is mimo ofdm programm

说明：  利用奇异值分解-总体最小二乘法估计ARMA模型的AR参数,并利用参数进行谐波恢复仿真程序(The use of singular value decomposition- total least squares estimation of AR parameters of ARMA model and using the parameters of harmonic retrieval simulation program)

说明：  针对LMS算法的FFE线性均衡器Matlab实现，以及性能分析。含有详细注释。(LMS algorithm for linear FFE equalizer Matlab implementation, and performance analysis. With detailed notes.)

这是一个不错的图像融合的Matlab程序,希望它能对你有所帮助.(This is a good image fusion Matlab procedures in the hope that it will be helpful to you.)

元胞自动机为使人员疏散离散模型更好描述行人微观特性，提出一种改进元胞自动机的人员疏散模型。(In order to make the discrete model of evacuation better describe the micro-characteristics of pedestrians, a new evacuation model based on improved cellular automata is proposed.)

LTE PUCCH source code(LTE uplink control channel)

压缩文件包含两部分，一部分为捷联惯导的基本内容，是.ppt，一共五章。还有一部分为捷联惯导的解算程序，共九个，是.m文件。用的时候需要将数据的txt文档放在文件夹内，运行test.m即可。(The compressed file contains two parts, one for the sins of the basic ppt, a total of five chapters. SINS solver, a total of nine, is the m files. Used when data txt file on the folder, run test.m can.)

Lighting Color Filter Test extends Test Case Source Code for Andriod.

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.)