pattern recognition and machine learning - Bishop

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.

平板流中，增加了障碍物，属于LBM学习的基础代码程序，很好理解。

Decision-making Trial and Evaluation Laboratory(DEMATEL)直译为决策实验室分析。DEMATEL 也有翻译成决策与试验评价实验室，或者简称实验室法。由于中文比较拗口，一般情况下，念[de mei tel] 或者念 [di mie tel]。1971 年在日内瓦的一次会议上美国 Battelle 实验室的学者 A. Gabus 和 E. Fontela 提出的为了解现实世界中复杂、困难的问题而提出的方法论，是一种运用图论和矩阵工具的系统分析的方法。通过系统中各要素之间的逻辑关系和直接影响矩阵，可以计算出每个要素对其它要素的影响度以及被影响度，从而计算出每个要素的原因度与中心度，作为构造模型的依据，从而确定要素间的因果关系和每个要素在系统中的地位。DEMATEL 是一种系统要素分析方法，通过分析系统各要素之间的逻辑关系，构建直接影响矩阵并对其进行相关计算，以此确定各要素对其他要素的影响度与被影响度，进而计算出中心度与原因度进一步揭示系统的结构关系。该方法在诸多复杂系统的因素重要性权重分析研究中有着相对成熟的应用

卡尔曼滤波松组合导航（ins_gps.m）

【实例简介】汉明码编码和译码的仿真代码

【实例简介】平方根卡尔曼滤波

牛顿法，输入目标函数、初始点、精度，能够得到整个求解过程，每一步迭代的结果都能打印出来，方便初学者学习，跟教材完全对应。

自组织映射 (SOM) 解决旅行商问题 (TSP)

智能微电网粒子群优化算法

可用于雷达信号、脉冲信号的幅度相位FFT分析，适合初学者仿真使用