实验三：典型环节特性及稳定性及稳态误差分析.docx

【实例简介】数学模型-超全模型汇总.zip 数学建模方法及应用、数学建模与数学实验、姜启源、灰色理论、人口预测、

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】《MATLAB在振动信号处理中的应用》是王济著、中国水利水电出版社，知识产权出版社出版发行的一本讲述借助简单、高效、功能强大的MATLAB系统实现振动数字信号的分析处理的图书。本书给出了大量的振动信号处理编程实例，以有助于读者快速学习和掌握MATLAB的编程技术，应用于实际的振动信号处理工作之中。

最小二乘法(ecf.m)

 1.编程实现对图像lena.bmp叠加均值为0，方差为0.02的高斯噪声，分别用邻域平均法和中值滤波法（窗口尺寸为3×3、5×5、15×15、35×35）对该图像进行滤波，显示叠加噪声前后的图像及滤波后的图像。 2. 编程实现对图像lena.bmp叠加椒盐噪声，选择合适的滤波器将噪声去除； 3. 编程实现频率域的理想低通滤波平滑：加噪，改变截止频率，观察效果。

模糊自适应PID控制是在PID算法的基础上，以误差e和误差变化率ec作为输入，利用模糊规则进行模糊推理，查询模糊矩阵表进行参数调整，来满足不同时刻的e和ec对PID参数自整定的要求。 【源码目录】 自适应模糊PID ├── Fuzzypid2.mdl ├── __Previews │   └── work222.mdlPreview ├── fight.mdl ├── fuzzyPID.fis ├── mohupid1.fis └── work222.mdl 1 directory, 6 files

【实例简介】稳态

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