信号与系统实训项目

该程序是关于神经网络的自适应控制器设计的仿真，能够运行

%由邻接矩阵画连接图%输入为邻接矩阵rel，必须为方阵；%control为控制量，0表示画出的图为无向图，1表示有向图。默认值为0

MATLAB信号处理 频谱分析加汉宁窗函数 源代码

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。

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.

信号与系统-陈后金-北京交通大学-全.ppt

Isight集成ProE ICEM CFX MATLAB示范.zip

基于贝叶斯优化的LSTM预测

【实例简介】平方根卡尔曼滤波

萤火虫群智能优化算法（Glowworm Swarm Optimization, GSO）是由K.N.Krishnanand和D.Ghose两位学者在2005年提出的一种通过模拟自然界中萤火虫发光行为而构造出的新型群智能优化算法。它模拟了自然界中萤火虫群中个体通过发光来吸引伙伴或觅食，萤火虫携带荧光素越多，萤火虫越亮，个体的吸引力越强，最终使得大部分萤火虫聚集在最亮的萤火虫所处位置上的这种现