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attachments_2010_11_25
QPSK Modulation and demodulation Project
- 2010-11-26 05:26:27下载
- 积分：1
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median~PSNR
例举了中值滤波，均值滤波等方法，以及用MSE和PSNR来判断图像质量。(Cites median filtering, average filtering method and the use of MSE and PSNR to judge image quality.)
- 2010-05-28 10:31:06下载
- 积分：1
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jiachuanglvboqi
这几个程序可以实现加窗后对信号滤波，包括凯泽窗，汉明窗，矩形窗(This several programs can realize add window to signal after filtering, including the Kaiser window, han Ming window, rectangular window
)
- 2011-12-29 19:41:39下载
- 积分：1
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new_srrc_one_cap_volterra_3rd_order_LMS
one cap 3rd order volterra nonlinear equalizer for vlc
- 2021-04-15 22:38:54下载
- 积分：1
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游标
pb的小例子,是PB中的游标的经品,实现查询功能.(pb small examples, PB cursor on the goods and realize the inquiry.)
- 2005-05-23 22:15:27下载
- 积分：1
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emd2_regression
说明： 基于核回归的图像散乱点插值，用于BEMD分解(scattered data interpolation based on kernel regression)
- 2011-03-24 13:15:13下载
- 积分：1
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region_grow1
区域增长法的Matlab实现,区域增长法的Matlab实现(Matlab to achieve regional growth law)
- 2011-04-28 15:42:56下载
- 积分：1
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HHT
把HHT和神经网络结合起来，识别出是否故障。对于HHT变换，这里用到的是它的IMF分解，然后用能量理论来判别哪些模组是虚假分量，哪些是是真实分量。对于EMD分解后的谱进行特征提取 ，利用的理论基础就是模糊熵。计算出真实 分量的模糊熵，作为输入层；输出层为两个神经元，为0（故障 ）1（正常 （正常 ）判别该信号是否出现故障。(The combination of HHT and neural network to identify whether the fault. For the HHT transform, here is the use of its IMF decomposition, and then use the energy theory to determine which module is false, which is true component. The theoretical basis for the feature extraction of the spectrum after EMD decomposition is fuzzy entropy. The fuzzy entropy of the real component is calculated, as the input layer, the output layer is two neurons, which is 0 (fault) 1 (normal) to determine whether the signal is faulty.)
- 2016-03-09 12:58:20下载
- 积分：1
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局部均值分解 LMD
说明： 局部均值分解，相比于emd好一点，自适应将信号分解几个物理量(Local mean decomposition, a little better than emd, adaptively decomposes the signal into several physical quantities)
- 2019-12-15 18:58:56下载
- 积分：1
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MATLAB
巴特沃斯低通滤波器的设计的matlab原程序如下(Butterworth low-pass filter design matlab the original procedures are as follows)
- 2009-01-01 13:52:20下载
- 积分：1
