knn定位算法

单相全桥Z源逆变器，带闭环控制，电压电流波形效果较好，欢迎交流学习。

【实例简介】matlab中输入疲劳应力时程，使用该程序即可输出应力幅计数

MATLAB神经网络30个案例分析[全文PDF]及随书源代码

matlab创建origin文件

传感器网络节点定位算法matlab代码（Centroid，APIT，DVHOP, Bounding Box，……共7个） 无线传感器网络无需测距定位算法matlab源代码。包括apit，dv-hop，amorphous在内的共7个range-free算法。在run.m里的算法选择部分可以选择需要运行的算法，算法的参数可以参考对应子目录里的说明。每个子目录里都有一个pdf文档，是算法的最原始描述。

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.

无人机群控制优化

有源噪声控制FxLMS算法

%输入：光栅长宽%输出：格雷码集合

神经网络代码