关键帧提取(edge_check0.m)

matlab可用于脑电信号处理的样本熵

匈牙利算法和murty算法的简介及MATLAB实现。

【实例简介】

【实例简介】 设计一个密码锁的控制电路，当输入正确代码时，输出开锁信号以推动执行机构工作，用红灯亮﹑绿灯熄灭表示关锁，用绿灯亮﹑红灯熄灭表示开锁; 在锁的控制电路中储存一个可以修改的4位代码，当开锁按钮开关(可设置成6 位至8位，其中实际有效为4位，其余为虚设）的输入代码等于储存代码时，开锁; 从第一个按钮触动后的5 秒内若未将锁打开，则电路自动复位并进入自锁状态，使之无法再打开，并发出报警信号。

仿真的AM调制信号的循环谱循环自相关函数

关于matlab进行数字图像处理实现车牌定位

【实例简介】光伏最大功率追踪.slx

用MATLAB2019直接运行main.m即可

RBF.m

论文《As-Projective-As-Possible Image Stitching with Moving DLT》中的拼接算法，对于视差图像拼接具有一定的鲁棒性，但是对特征点数量及其分布均匀性有较高的要求。 The success of commercial image stitching tools often leads to the impression that image stitching is a “solved problem”.The reality, however, is that many tools give unconvincing results when the input photos violate fairly restrictive imaging assumptions;the main two being that the photos correspond to views that differ purely by rotation, or that the imaged scene is effectively planar.Such assumptions underpin the usage of 2D projective transforms or homographies to align photos. In the hands of the casual user,such conditions are often violated, yielding misalignment artifacts or “ghosting” in the results. Accordingly, many existing imagestitching tools depend critically on post-processing routines to conceal ghosting. In this paper, we propose a novel estimationtechnique called Moving Direct Linear Transformation (Moving DLT) that is able to tweak or fine-tune the projective warp toaccommodate the deviations of the input data from the idealized conditions. This produces as-projective-as-possible image alignmentthat significantly reduces ghosting without compromising the geometric realism of perspective image stitching. Our technique thuslessens the dependency on potentially expensive postprocessing algorithms. In addition, we describe how multipleas-projective-as-possible warps can be simultaneously refined via bundle adjustment to accurately align multiple images for largepanorama creation.