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基于ADMM的图像盲复原算法
【实例简介】
- 2021-05-18 10:32:36下载
- 积分：1
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水平极化方向图
水平极化方向图，各种天线水平极化方向图参数代码，对研究天线极化很有帮助
- 2020-12-03下载
- 积分：1
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matlab实现扫频信号生成音频
matlab实现扫频信号生成音频
- 2020-12-04下载
- 积分：1
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pdw参数产生代码（有注释）
检测到10048个脉冲：toa,pw以当前点数定义脉冲 1： TOA= 1030.00,PW= 810.00,PA=4569.326,MF= 28.111MHz脉冲 2： TOA= 1191.00,PW=1476.00,PA=6549.591,MF= 35.730MHz脉冲 3： TOA= 1289.00,PW=1484.00,PA=7356.821,MF= 23.770MHz雷达信号分选仿真数据产生
- 2021-05-07下载
- 积分：1
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L0问题求解OMP工具包
L0问题求解OMP工具包
- 2021-05-06下载
- 积分：1
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机器学习中的多示例包层次SVM分类算法
【实例简介】机器学习中的多示例包层次SVM分类算法
【核心代码】Bag_KI_SVM.m
KI-SVM
├── Bag KI-SVM
│ ├── Bag_KISVM_prediction.m
│ ├── Bag_KI_SVM.m
│ ├── Find_y.m
│ ├── Find_y_linear.m
│ ├── Max_Violated_y_set.m
│ ├── Readme.htm
│ ├── celltomatrix.m
│ ├── genIndex.m
│ └── normalization_gaussian.m
├── Instance KI-SVM
│ ├── Find_y.m
│ ├── Find_y_linear.m
│ ├── Inst_KISVM_prediction.m
│ ├── Inst_KI_SVM.m
│ ├── Max_Violated_y_set.m
│ ├── Readme.htm
│ ├── celltomatrix.m
│ ├── genIndex.m
│ └── normalization_gaussian.m
├── experiments.m
├── experiments_KISVM_musk1.m
├── libsvm-mat-2.88-MI-svm
│ ├── COPYRIGHT
│ ├── Makefile
│ ├── README
│ ├── doc.txt
│ ├── heart_scale.mat
│ ├── make.asv
│ ├── make.m
│ ├── read_sparse.c
│ ├── read_sparse.mexw32
│ ├── read_sparse.mexw64
│ ├── svm.cpp
│ ├── svm.cpp.bak
│ ├── svm.h
│ ├── svm.h.bak
│ ├── svm.obj
│ ├── svm_model_matlab.c
│ ├── svm_model_matlab.c.bak
│ ├── svm_model_matlab.h
│ ├── svm_model_matlab.obj
│ ├── svmpredict.c
│ ├── svmpredict.mexw32
│ ├── svmpredict.mexw64
│ ├── svmtrain.c
│ ├── svmtrain.c.bak
│ ├── svmtrain.mexw32
│ └── svmtrain.mexw64
└── normedmusk1.mat
3 directories, 47 files
- 2021-07-07 00:32:06下载
- 积分：1
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APAP（As Projective As Possible）视差鲁棒的图像拼接算法
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.
- 2020-11-30下载
- 积分：1
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偶极子天线MATLAB仿真
仿真偶极子天线，包括方向性图的三维图和H面、E面图
- 2021-05-06下载
- 积分：1
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FM信号的调制与解调对比分析（fmsignal2.m）
FM信号在103.5MHz载波上的调制，通过高斯信道后将原来的调制信号解调出来
- 2021-05-06下载
- 积分：1
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三倍频相位匹配(phase.m)
用于非线性光学三倍频过程中，计算相位匹配
- 2021-05-06下载
- 积分：1
