rocket4

通过利用雷达脉冲宽度与信噪比关系公式，分析雷达在三咱不同检测目标距离下的信噪比与脉冲宽度关系。(Through the use of the radar pulse width of the signal-to-noise ratio relationship formula to analyze the radar in three different detection target distance we signal-to-noise ratio and pulse width relationship.)

PCM clustering algorithm

测量稀土元素的光谱的matlab程序,可以作图，十分简单方便(REE spectra measurements matlab program, you can plot is very simple and convenient)

运用多尺度自卷积计算图像的仿射不变矩的方法，该方法新颖，具有一定的创新性(Using multi-scale image from the convolution calculation of affine invariant moment method, which is novel, has some innovative)

matlab 误差与范数 现行版本较少 吉林大学应用数学学院老师讲稿 今后会陆续上传(matlab error and norm of the current version of Applied Mathematics, Jilin University, Institute of fewer teachers will continue upload the script in the future)

前后向平滑， music 主要包含经典music算法实现原理及其代码，然后在此基础上介绍了前后向平滑算法的实现及其代码和仿真结果(forward/backward spatial smoothing，MUSIC Consists mainly of classical music algorithm theory and its code, and then on this basis introduced before and after smoothing algorithm and code and simulation results)

此matab函数文件可以用来计算模型的李雅普诺夫指数，用于稳定性分析。(this Lyapunov.m file can be used to compute the lyapunov exponential)

matlab与C混合编程的实例，求解两个矩阵的和。(An example of matlab-C mixed programming,getting the adding solution of two matrixes.)

说明：  小波分析 图像融合 决策树分类 matlab 源代码 (fusion image, classify)

包括kf，ekf，pf，upf可以自己定制模型参数，完成滤波(ReBEL currently contains most of the following functional units which can be used for state-, parameter- and joint-estimation: Kalman filter Extended Kalman filter Sigma-Point Kalman filters (SPKF) Unscented Kalman filter (UKF) Central difference Kalman filter (CDKF) Square-root SPKFs Gaussian mixture SPKFs Iterated SPKF SPKF smoothers Particle filters Generic SIR particle filter Gaussian sum particle filter Sigma-point particle filter Gaussian mixture sigma-point particle filter Rao-Blackwellized particle filters The italicized algorithms above are not fully functional yet (or included in the current release), but will be in the next or future releases. The code is designed to be as general, modular and extensible as possible, while at the same time trying to be as computationally efficient as possible. It has been tested with Matlab 7.2 (R2006a). )