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simulink仿真源码，一定会对你有所帮助！(The simulink program is helpfull for you!)

这里我们针对三级固体火箭进行研究，主要考虑每一级发动机工作时推力 和比冲 与发动机试车存在摄动偏差（相差 ）时所产生火箭关机点时刻的状态偏差。火箭的飞行的动力学方程可建立在地面发射坐标系中，火箭的第一级、第二级和第三级按照固定的俯仰角程序飞行，第二、三级飞行时已在大气层外，此时可忽略气动力的影响。(Here we study for three solid rocket, the main consideration at every level when the engine thrust and state arising the moment the rocket off point perturbation deviation (difference) in the presence of specific impulse and engine test bias. Outside of the rocket flight dynamics equations can be established on the ground coordinate system launch, the rocket s first stage, the second and third stages according to a fixed elevation angle of flight procedures, and the second, when the third flight already in the atmosphere, this when can ignore the effects of gas dynamics.)

时反程序,用于计算信号的时间反转镜，编的挺好的(TRM programme)

支持向量机的matlab程序实现，可用于模式分类，模式识别(SVM matlab program can be used for pattern classification, pattern recognition)

大名鼎鼎的Patton的copula工具箱，不知道各位有没有(The famous Patton of the copula toolbox, do not know if you have any)

Date time picker in matlab

对16进制的QAM调制信号的matlab仿真 已完美运行通过(On the 16-band QAM modulated signal matlab simulation has been run through a perfect)

Fast calculation of elastic response spectra

overlapped image segmentation the code can also be found at matlabcentral

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.)