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zernikemoment
ZK矩的计算程序,有MATLAB和C语言两部分。ZK矩在形状识别和分析中有重要应用,可以在特征参数提取中经常使用。(ZK moment calculation procedure, MATLAB and C language has two parts. ZK moments in shape recognition and analysis has important applications, feature extraction can be often used.)
- 2007-10-03 15:23:07下载
- 积分:1
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MATLABGUI
【程序】 MATLAB GUI 设计在大学物理中的应用(MATLAB GUI)
- 2009-10-16 11:18:12下载
- 积分:1
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ls_svm
支持向量机在波束形成中的一种应用
能够形成波束,且效果很好.(SVM in the beamforming application to form a beam, and the results very good.)
- 2021-02-19 16:19:44下载
- 积分:1
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lung
Matlab图像处理,点检测、线检测、边缘检测、边缘连接,阈值处理。
(Matlab image processing, detection, line detection, edge detection, edge linking, the threshold processing.)
- 2012-05-21 18:39:10下载
- 积分:1
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matlabdaima
P0303:采用灰度变换的方法增强图像的对比度
P0304:直方图均匀化
(P0303: using gray transform method to enhance the contrast of the image P0304: histogram equalization)
- 2013-07-09 11:10:35下载
- 积分:1
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article
软件程序按照发射端所掌握的各用户信道状态信息的程度共分为两部分:即完整信道状态信息(CSIT)和部分信道状态信息(CSIP)。其中,每一部分都包括预编码(precoding)和用户调度(scheduling)
在CSIT中,precoding又按照各用户的数据流数分为单数据流和多数据流两种情况。在每种情况下,首先考察了不同预编码算法的性能表现,包括两种ZF、MMSE、SINR、SLNR。之后又考察了功率分配算法的性能表现(文件名中含有PD表明其含有功率分配的过程)。按照不同指标进行功率分配的,在文件名中进行了区分,如PD_CN代表以信道范数为参考指标进行功率分配。Scheduling部分首先观察了RoundRobin、MaxH和MMSLNR三种算法的性能对比。之后在Kc和Round部分分别观察了不同预选用户数和不同最大替换轮数下MMSLNR算法的表现。
在CSIP中,只对各用户单数据流的情况进行了仿真。采用的预编码算法主要有DSLNR(即直接运用CSIT下的预编码算法)、ESLNR(即对SLNR进行均值计算的,在CSIP中,引入均值计算的与SLNR有关的算法,其文件名中都有modified以示区别)、EMMSE(即陈明老师那边的那篇文章中的预编码算法)。Scheduling中也只是简单的观察了RoundRobin、MaxH、DMMSLNR和EMMSLNR(前者没有均值计算,后者有)的性能对比。(The degree of channel state information for each user software program in accordance with the master transmitter consists of two parts : the complete channel state information (CSIT) and partial channel state information (CSIP). Wherein , each of which comprises a pre- coding (precoding) and the user scheduling (scheduling)
In CSIT in , precoding and each user according to the number of data streams into a single data stream and multiple data streams in both cases . In each case , first examine the performance of different pre- coding algorithm, including two ZF, MMSE, SINR, SLNR. After they inspected the power allocation algorithm performance ( file name contains PD showed that it contained power allocation process ) . According to different indicators for power distribution , make a distinction in the file name , such as PD_CN representative channel norm-referenced index for power distribution . Scheduling section first observed the performance comparison RoundRobin, MaxH and MMSL)
- 2021-02-04 15:29:58下载
- 积分:1
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image_change_detecting
图像变化检测算法,由t检验得到差分图像的变化掩膜。左后成功检测到图像中运动的物体。(Image change detection algorithms have been tested by the t change difference image mask. Left a successful campaign to detect objects in images.)
- 2009-04-25 10:04:10下载
- 积分:1
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fault_detection_filter
涉及故障诊断方面的故障检测观测器,附有参考文献(fault detection filter in the fault diagnosis area, with a reference paper)
- 2010-12-14 20:56:50下载
- 积分:1
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control_for_robotic_manipulator
说明: 这是一个matlab控制仿真小程序,对初学者有一定帮助!(This is a small Matlab simulation control procedures for beginners will definitely help!)
- 2006-02-15 22:03:35下载
- 积分:1
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sift
1 SIFT 发展历程
SIFT算法由D.G.Lowe 1999年提出,2004年完善总结。后来Y.Ke将其描述子部分用PCA代替直方图的方式,对其进行改进。
2 SIFT 主要思想
SIFT算法是一种提取局部特征的算法,在尺度空间寻找极值点,提取位置,尺度,旋转不变量。
3 SIFT算法的主要特点:
a) SIFT特征是图像的局部特征,其对旋转、尺度缩放、亮度变化保持不变性,对视角变化、仿射变换、噪声也保持一定程度的稳定性。
b) 独特性(Distinctiveness)好,信息量丰富,适用于在海量特征数据库中进行快速、准确的匹配[23]。
c) 多量性,即使少数的几个物体也可以产生大量SIFT特征向量。
d) 高速性,经优化的SIFT匹配算法甚至可以达到实时的要求。
e) 可扩展性,可以很方便的与其他形式的特征向量进行联合。
4 SIFT算法步骤:
1) 检测尺度空间极值点
2) 精确定位极值点
3) 为每个关键点指定方向参数
4) 关键点描述子的生成
本包内容为sift算法matlab源码(1 SIFT course of development
SIFT algorithm by DGLowe in 1999, the perfect summary of 2004. Later Y.Ke its description of the sub-part of the histogram with PCA instead of its improvement.
2 the SIFT main idea
The SIFT algorithm is an algorithm to extract local features in scale space to find the extreme point of the extraction location, scale, rotation invariant.
3 the main features of the SIFT algorithm:
a) SIFT feature is the local characteristics of the image, zoom, rotate, scale, brightness change to maintain invariance, the perspective changes, affine transformation, the noise also maintain a certain degree of stability.
b) unique (Distinctiveness), informative, and mass characteristics database for fast, accurate matching [23].
c) large amounts, even if a handful of objects can also produce a large number of SIFT feature vectors.
d) high-speed and optimized SIFT matching algorithm can even achieve real-time requirements.
e) The scalability can be very convenient fe)
- 2012-05-25 15:31:16下载
- 积分:1