匹配滤波

图像结构相似性评估指标的matlab代码

该模型大致基于T.Athay等人提出的IEEE 39总线系统，用于面向研究的研究和教育目的。该基准的SimPowerSystems实现的作者是IREQHydro-Québec研究所的Ali Moeini和Innocent Kamwa。参考文献A. Moeini，I。Kamwa，P。Brunelle，G。Sybille，“在SimpowerSystems中实现的开放数据IEEE测试系统，用于电网动力学和控制的教育和研究”，电力工程大会（UPEC），2015年第50届国际大学，2015年9月1-4日，英国斯塔福德郡大学。http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7339813&tag=1

MATLAB实现ARQ重传，实现时延的加入及重传次数的自定义改动，注释详尽，对初学者有一定的帮助

简洁易懂的matlab版ply彩色模型生成工具，只需要输入点云的坐标矩阵和对应的彩色RGB数组，即可生成二进制的ply文件，代码通俗易懂，十分便捷。

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.

【实例简介】

机器学习中常用的基本算法：K－近邻法(KNN)

【实例简介】模式识别与机器学习经典书籍的配套代码Ch01-demo

3机九节点(d_009_fault_mdl.m)

基于递归最小二乘算法在线辨识锂离子电池一阶模型参数