228336serial-matlab

一个自己写的设置SNAKE初始节点的MATLAB程序,以绿色十字标记节点位置,在此基础上可以编制自己的SNAKE算法,(himself wrote a set of Snake initial nodes MATLAB procedures to Green Cross markings node location, on this basis can prepare their own Snake algorithm, huh)

条带SAR成像程序，基础程序，但是很重要，可惜学习下！(Band SAR imaging procedures)

极大似然估计定位的编程实现，误差分析，节点数仿真等，比较全面，适合初学者(Maximum Likelihood Estimation targeted programming, error analysis, simulation, and other nodes, a more comprehensive, suitable for beginners)

该程序通过感知器实现布尔逻辑运算，具体实现与或还有异或的运算(The program through the sensor to achieve Boolean logic operations)

利用matlab实现绘图文档Drawing documents using matlab implementation(Using matlab to achieve drawing document Drawing documents using matlab implementation)

It is Radar System design and signal processing matlab code. It provides varios detalail of standard Signal Radar signal processing algorithm .

盲均衡1，采用的自适应算法为横模算法 （blind1cma）()

this matlab code operate histogram equalization based on probability

最速梯度法工具箱，添加方法在命令窗口中敲入pathtool，会出现一个setpath的窗口，点add folder或者add with subfolders按钮，选中你的工具箱。保存既可。任选工具箱中的一个命令，然后help一下看看是否好使。(Toolbox steepest gradient method, add the method in the command window and typing pathtool, a setpath window appears, point add folder or add with subfolders button, select your toolbox. Save both. Choose a command in the toolbox, and then help look to see if so.)

大量实验表明,提出的方法对同种传感器或者不同传感器图像之间的配准都是有效的。 提出了一种新的基于角点检测的图像配准方法,其核心思想是采用一种快速的 基于图像灰度的角点检测新算法,通过沿圆弧曲线扫描获取角点信息,然后根据这些 角点信息建立图像间角点的对应关系,并由此得到初配准参数,最后通过迭代过程以 提高配准的精度. 理论分析和实验结果表明,该算法对图像间的旋转角度没有限制, 配准精度高而且计算量较小. (Experiments show that the proposed method on the same kind of sensor or between the different sensor image registration is valid. A new corner detection based image registration method, the core idea is to use a fast gray-based new algorithm for corner detection, scanning through the curve along the arc for corner information, and then based on these corner information to establish image correspondence between the corners, and thus be the beginning of registration parameters, and finally through the iterative process to improve the accuracy of registration. Theoretical analysis and experimental results show that the algorithm is rotation between the image does not limit , registration accuracy and less computation.)