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8FSK_BER
8FSK的调制信号的产生、理论误码率及实际误码率统计分析(8FSK modulation signal s theoretical and actual BER analysis)
- 2021-03-15 22:19:22下载
- 积分：1
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mdbf
capon算法，用于波束形成，应与工程或者研究都可以(capon algorithm for beamforming, and engineering or research should be)
- 2009-05-29 10:14:05下载
- 积分：1
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RTLS-CM
基于雷达定位的高精度无线定位系统，一维精度可达1cm，二维精度可达5cm(High-precision radar-based wireless location positioning system, the one-dimensional accuracy of up to 1cm, dimensional accuracy is up to 5cm)
- 2011-05-12 19:42:42下载
- 积分：1
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Bai
白志东给出的对于高维数据两总体均值检验的程序，可以参考下(high dimension)
- 2014-09-20 18:24:47下载
- 积分：1
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NoiseLevel20140507
A MATLAB code of noise level estimation in images
- 2014-12-20 20:50:34下载
- 积分：1
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spectrumcorrectenergymethodshare
离散频谱校正，采用加hanning窗的能量重心法校正，程序已实际验证(Discrete spectrum correction, correction with adding hanning window energy gravity method, program has been the actual authentication)
- 2021-04-15 23:28:54下载
- 积分：1
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PAPR-for-OFDM
OFDM峰均比经典算法matlab程序，包括PTS，SLM，限幅等(OFDM PAPR reducing source codes,including PTS SLM and Cliping)
- 2020-11-16 23:19:40下载
- 积分：1
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SIFT
经典的SIFT算法，实现高效高精度的图像匹配
matlab编写，内涵详尽注释，以及用法说明的txt文件，另加试验文件(Classic SIFT algorithm to achieve high efficiency and precision of image matching matlab prepared connotation detailed notes, as well as usage instructions txt file, plus a test file)
- 2014-01-03 19:59:09下载
- 积分：1
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ACSMCFuzzySMC
利用模糊控制結合滑模控制合成的模糊滑模控制器，應用在磁浮軸承系統。(The use of fuzzy control with sliding mode control synthesis of fuzzy sliding mode controller, used in magnetic bearing systems.)
- 2009-12-14 16:22:47下载
- 积分：1
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work
matlab 关于association rule 的自己写的函数，有3个文件,
association.m：h = association(m, i, j)
i=>j, m是数据，h是support和confidence，该函数只适用于单个数据
ass_item: h=ass_itset(m, a, b)
同上，但是可用于多个数据（m为数组）
assrule: h = assrule(m, threshold1, threshold2)
该函数用于classification， 得到规则，threshold1为要求的support,threshold2为要求的confidence，h 则为符合要求的规则及其support和confidence，前2列为规则，后2列为其support和confidence
(matlab on the association rule to write functions, there are 3 files, association.m: h = association (m, i, j) i => j, m is the data, h is the support and confidence, this function applies only to a single Data
ass_item: h = ass_itset (m, a, b) it is the same as above, but it can be used for multiple data (m can be matrix)
assrule: h = assrule (m, threshold1, threshold2) the function used for classification,get the rules, threshold1 is the require of support, threshold2 is the required of confidence, h is the rules and their support and confidence, the former two columns as a rule, the latter two columns as one of its support and confidence)
- 2009-12-15 02:51:44下载
- 积分：1
