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Digital_Signal_Processing_Using_Matlab
ebook about Digital Signal Processing Using Matlab
- 2009-03-05 17:51:29下载
- 积分：1
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Template Classes
Template Classes的用法(Template usage)
- 2005-02-25 21:31:42下载
- 积分：1
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MUSIC-source-based-decorrelation
MUSIC算法是基于天线阵列协方差矩阵的特征分解类DOA估计算法，这里给出的是基于解相干的MUSIC算法。(MUSIC algorithm is based on the antenna array covariance matrix eigen-decomposition DOA estimation algorithm presented here is based on the MUSIC algorithm decoherence.)
- 2014-01-06 15:30:37下载
- 积分：1
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music_advanced
说明： 在现代信号处理领域非常重要的方法。这是最新的改进算法！(in modern signal processing field is very important way. This is the latest improved algorithm!)
- 2006-04-28 11:23:03下载
- 积分：1
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WinerHopf
Winer Hopf自适应算法的仿真,信源为窄带信号,高斯白噪声(Winner Hopf adaptive algorithm simulation, the source for narrow-band signals, Gaussian white noise)
- 2007-06-14 18:24:01下载
- 积分：1
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rolling_cart_with_air_drag
rolling cart with air drag force simulink matlab block diagram
- 2013-02-27 17:47:22下载
- 积分：1
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Fisher
MATLAB实现Fisher线性分类实验，未调用现有函数。(MATLAB the Fisher Linear classification experiment, did not call the existing functions.)
- 2013-01-05 14:59:00下载
- 积分：1
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power_FCV_powertrain
simulation of train in matlab with fuel cell source
- 2013-09-08 15:34:22下载
- 积分：1
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split_fourier_method
Metodo Split-Step Fourier for Light Beam in Single Mode Optics Fiber Waveguide
- 2011-04-21 20:15:29下载
- 积分：1
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VistaRestoreTools1.0
denoise
In BayesShrink[5] we determine the threshold for
each subband assuming a Generalized Gaussian
Distribution(GGD) . The GGD is given by
GG¾ X ¯ (x) = C(¾ X ¯ )exp¡ [® (¾ X ¯ )jxj]¯ (6)
¡ 1 < x < 1 ¯ > 0, where
® (¾ X ¯ ) = ¾ ¡ 1
X [ ¡ (3=¯ )
¡ (1=¯ ) ]1=2
and
C(¾ X ¯ ) = ¯ ¢ ® (¾ X ¯ )
2¡ ( 1
¯ )
and ¡ (t) =
R1
0 e¡ uut¡ 1du.
The parameter ¾ X is the standard deviation and ¯
is the shape parameter It has been observed[5] that
with a shape parameter ¯ ranging from 0.5 to 1, we
can describe the the distribution of coefficients in a
subband for a large set of natural images.Assuming
such a distribution for the wavelet coefficients, we empirically
estimate ¯ and ¾ X for each subband and try
to find the threshold T which minimizes the Bayesian
Risk, i.e, the expected value of the mean square error.
- 2012-06-08 01:38:48下载
- 积分：1
