Centralized_EKF

用最小二乘法反应雷达得到的图像，得到各种数据特征参数(Reaction of the least square method to obtain the radar image data to obtain various characteristic parameters)

cordic算法的matlab仿真，小波包分析提取振动信号中的特征频率，微分方程组数值解方法。( cordic matlab simulation algorithm, Wavelet packet analysis to extract vibration signal characteristic frequency, Numerical solution of differential equations method.)

点云数据读取，以及运用四元素法进行坐标变换。(Point cloud data reading, and the use of four elements for coordinate transformation.)

code for blind channel equalization

gause-jordan method it is m-file

说明：  matlab经典算法的介绍与提高的法门！(classical algorithm matlab introduction and enhancement of the key!)

在运动的位置叠加噪声。进行JPDA概率数据关联及kalman滤波。 两运动目标在x-y平面做匀速直线运动。初始位置是（4000,1200）（300,1500）速度分别是（200,200）（400,200）传感器对量目标进行位置状态量测。 采样间隔T=1,点数n=80.检测概率为1，正确量测落入跟踪内的概率为0.99，杂波均匀分布的密度为2个/km2由RAND函数产生在[0，1]上均匀分布的随机变量，跟踪门限为9.21。 (Superimposed noise in the position of the movement. JPDA probabilistic data association and kalman filtering. Two moving targets uniform linear motion in the xy plane. The initial position (4000,1200) (300,1500) speed (200,200) (400,200) position sensor on the amount of target state measurements. Sampling interval T = 1, points n = 80. Detection probability of correctly measured fall into the tracking probability 0.99, 2/km2 clutter uniform distribution of density generated by the RAND function [0,1] uniformly distributed random variables tracking threshold of 9.21.)

大型邮轮的matlab实现 我觉得很有用 其中有详细的源代码 和英文注释(Matlab implementation of large cruise ships which I find very useful and detailed source notes in English)

Matlab Edge detection using masks

Useful tool for rendering and outputting information rich images(This function can be used in place of IMAGE, IMAGESC and IMSHOW, but does so much more. It is fast and displays images as they should be- correct aspect ratio, integer magnification, no axes. In addition, it can return the image as an output variable- useful for saving to disk, texture mapping surfaces, and post-rendering manipulation such as overlaying/combining two or more images. All the MATLAB built-in colormaps are implemented, but without MATLAB s nasty discretization artifacts. Plus, there are many new colormaps which are helpful for viewing more complex data, such as optic flow, likelihoods over images, difference images, segmentations, stereo image pairs (as anaglyphs) and edge-maps with orientation. It also accepts user defined linear and non-linear colormaps.)