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AWGNOFDM
基于AWGN信道的OFDM仿真程序,欢迎下载参考相互学习!(Based on the AWGN channel OFDM simulation program are welcome to download a reference to learn from each other!)
- 2007-08-10 21:35:24下载
- 积分:1
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spatiograms
matlab code for spatiograms of images
- 2010-12-30 01:47:35下载
- 积分:1
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229938746
说明: 可进行位置识别,通过声源的波束形成,可知道其相关信息.再加上(can identify the location, source, a beam forming, know relevant information. Plus )
- 2006-05-16 23:42:03下载
- 积分:1
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matlab
将带噪声的音频文件中的噪声滤除掉,得到原始音频信号(The noisy audio file noise filtered out to obtain the original audio signal)
- 2015-03-06 15:22:06下载
- 积分:1
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textin2
DWT音频水印嵌入算法程序,DWT音频水印嵌入算法程序,DWT音频水印嵌入算法程序(Audio watermarking algorithm in DWT DWT audio watermarking algorithm, DWT audio watermarking algorithm)
- 2013-05-10 20:14:17下载
- 积分:1
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Generalized-Predictive-Control
Generalized Predictive Control Algorithm
- 2015-04-19 06:55:00下载
- 积分:1
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FBMC_OFDM_Prototype
FBMC prototype filter for 5g communications through wireless interface.
- 2016-07-08 19:07:59下载
- 积分:1
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TFRGABOR
伪魏格勒分布源代码.适合于非稳态的时频联合分析,可直接用于MATLAB编程,无解压密码.(pseudo-source code distribution. Suited to the non-steady-state joint time-frequency analysis can be used directly in MATLAB programming, without extracting passwords.)
- 2006-11-23 15:18:19下载
- 积分:1
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ofdm--outer
ofdm调制信号Matlab仿真生成代码 压缩包内为.m文件可直接用matlab打开(ofdm outer)
- 2013-12-24 10:30:07下载
- 积分:1
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matlab
聚类算法,不是分类算法。分类算法是给一个数据,然后判断这个数据属于已分好的类中的具体哪一类。聚类算法是给一大堆原始数据,然后通过算法将其中具有相似特征的数据聚为一类。这里的k-means聚类,是事先给出原始数据所含的类数,然后将含有相似特征的数据聚为一个类中。所有资料中还是Andrew Ng介绍的明白。首先给出原始数据{x1,x2,...,xn},这些数据没有被标记的。初始化k个随机数据u1,u2,...,uk。这些xn和uk都是向量。根据下面两个公式迭代就能求出最终所有的u,这些u就是最终所有类的中心位置。(Clustering algorithm, not a classification algorithm. Classification algorithm is to give a figure, and then determine the data belonging to a specific class of good which category. Clustering algorithm is to give a lot of raw data, and then through the algorithm which has similar characteristics data together as a class. Here k-means clustering, is given in advance the number of classes contained in the raw data, then the data contain similar characteristics together as a class. All information presented in or Andrew Ng understand. Firstly, raw data {x1, x2, ..., xn}, the data is not labeled. K random initialization data u1, u2, ..., uk. These are the vectors xn and uk. According to the following two formulas can be obtained final iteration all u, u is the ultimate all these classes the center position.)
- 2014-02-18 09:59:02下载
- 积分:1