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fit_ML_laplace
fit_ML_normal - Maximum Likelihood fit of the laplace distribution of i.i.d. samples!.
Given the samples of a laplace distribution, the PDF parameter is found
fits data to the probability of the form:
p(x) = 1/(2*b)*exp(-abs(x-u)/b)
with parameters: u,b
format: result = fit_ML_laplace( x,hAx )
input: x - vector, samples with laplace distribution to be parameterized
hAx - handle of an axis, on which the fitted distribution is plotted
if h is given empty, a figure is created.
output: result - structure with the fields
u,b - fitted parameters
CRB_b - Cram?r-Rao Bound for the estimator value
RMS - RMS error of the estimation
type - ML
- 2011-02-09 19:06:32下载
- 积分：1
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DemoPackage.tar
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Smart-Antennas-for-Wireless-Communications
the book is about designing smart antennas for wireless communications
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- 积分：1
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item
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- 积分：1
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jacenc
JPEG AC coefficient encoding routine
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