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BinRSM
说明: 这个程序可以用于全局细分,将响应面细分之后再进行回归操作。(This program can be applied for d-RSM.)
- 2010-04-09 17:08:13下载
- 积分:1
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RSAMultiPrimePrivateCrtKeyImpl
Additional class for verification RSAMultiPrimePrivateCrtKey interface.
- 2013-12-16 11:34:02下载
- 积分:1
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Segmentation
基于直方图的自适应阈值法实现分割图像前景与背景,matlab编写,包含测试图像和实验报告(Foreground and background to achieve image segmentation histogram-based adaptive threshold method, matlab prepared, containing the test images and test reports)
- 2014-01-08 15:35:05下载
- 积分:1
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ukfkf2
UKF和KF的实现。并通过输出图像比较两者的区别(UKF and the KF implementation. By comparing the difference between the output image)
- 2011-04-29 15:34:23下载
- 积分:1
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singlehex2num
Convert single precision IEEE hexadecimal string to number. By Matthias Nö ll.
- 2013-07-31 09:22:17下载
- 积分:1
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200910045186
关于可配置长度的DFT的专利 非常值得学习(Configurable length DFT )
- 2011-05-30 00:57:37下载
- 积分:1
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(source)
时频分析程序,包括一些应用实例还有一些源程序(Time-frequency analysis process, including application examples and some source code)
- 2011-12-12 20:57:18下载
- 积分:1
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v06_03_dem_2up_arrange
一个OFDM符号128个有效符号,插入128个虚拟子载波
符号率(即有效数据率)fsymbol,而发送速率(需要包括虚拟子载波)2fsymbol
输入的数据需要2倍的发送数据率,以便进行内插,实现位定时跟踪,即4倍fsymbol采样率的调制信号
OFDM symbol Nfft=128 points
一个OFDM符号数据点 Nfft*2 = 256 , Guard Interval点 =Ng*2=64
(128 of an OFDM symbol of a valid symbol 128 inserted virtual sub-carrier
Symbol rate (the effective data rate) fsymbol sending rate (including virtual subcarriers) 2fsymbol
Of the input data needs to be 2 times the transmission data rate, in order to carry out the interpolation, to achieve the bit timing tracking, i.e. four times the sampling rate modulation signal fsymbol
OFDM symbol Nfft = 128 points
One OFDM symbol data points nfft* 2 = 256, the Guard Interval dot = Ng* 2 = 64)
- 2013-05-05 17:13:09下载
- 积分:1
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sun-radiation
用于简单计算照射到地表的太阳辐照度,可以模拟任意的精度、纬度、高度的太阳太阳辐照度(Exposure to the surface for the simple calculation of the amount of solar radiation)
- 2012-01-10 08:59:17下载
- 积分:1
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duoshili
考虑到传统的多示例多标签框架忽略了标签相关性,或者是将标签相关性作为全局概念知识加以利用,我们将局部标签相关性引入到MIML一SVM多示例多标签学习框架中来,得到了一种新的多示例多标签学习算法MIML LC SVM(Taking into account the traditional multi-sample multi-label framework ignores the label correlation or correlation between the label to be used as a global concept of knowledge, we will bow} local label correlation MIML into a multi-instance multi-label SVM learning framework in the past, get a new multi-instance multi-label learning algorithm MIML LC SVM)
- 2015-04-13 16:08:02下载
- 积分:1