mirror of https://github.com/saitohirga/WSJT-X.git
Fix misprints in equation 4 and 5
git-svn-id: svn+ssh://svn.code.sf.net/p/wsjt/wsjt/branches/wsjtx@6313 ab8295b8-cf94-4d9e-aec4-7959e3be5d79
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@ -392,7 +392,7 @@ tric probability distribution.
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\begin_layout Standard
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\begin_layout Standard
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\begin_inset Formula
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\begin_inset Formula
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\begin{equation}
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\begin{equation}
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P(x=\epsilon|N,X,s)=\frac{\binom{X}{x}\binom{N-X}{s-\epsilon}}{\binom{N}{s}}\label{eq:hypergeometric_pdf}
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P(x=\epsilon|N,X,s)=\frac{\binom{X}{\epsilon}\binom{N-X}{s-\epsilon}}{\binom{N}{s}}\label{eq:hypergeometric_pdf}
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\end{equation}
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\end{equation}
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\end_inset
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\end_inset
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@ -456,7 +456,7 @@ hygepdf(
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errors is
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errors is
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\begin_inset Formula
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\begin_inset Formula
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\begin{equation}
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\begin{equation}
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P(x\ge\epsilon|N,X,s)=\sum_{j=\epsilon}^{N}P(x=j|N,X,s).\label{eq:cumulative_prob}
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P(x\ge\epsilon|N,X,s)=\sum_{j=\epsilon}^{s}P(x=j|N,X,s).\label{eq:cumulative_prob}
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\end{equation}
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\end{equation}
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\end_inset
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\end_inset
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@ -735,7 +735,7 @@ and
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\end_inset
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\end_inset
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of the symbol's fractional power
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of the symbol's fractional power
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\begin_inset Formula $p_{1,\,j}$
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\begin_inset Formula $p_{1,\, j}$
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\end_inset
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\end_inset
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in a sorted list of
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in a sorted list of
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@ -878,7 +878,7 @@ and
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\begin_layout Standard
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\begin_layout Standard
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\begin_inset Formula
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\begin_inset Formula
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\[
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\[
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u=\frac{1}{n}\sum_{j=1}^{n}S(c_{j},\,j).
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u=\frac{1}{n}\sum_{j=1}^{n}S(c_{j},\, j).
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\]
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\]
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\end_inset
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\end_inset
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@ -911,7 +911,7 @@ The correct JT65 codeword produces a value for
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bins containing noise only.
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bins containing noise only.
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Thus, if the spectral array
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Thus, if the spectral array
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\begin_inset Formula $S(i,\,j)$
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\begin_inset Formula $S(i,\, j)$
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\end_inset
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\end_inset
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has been normalized so that its median value (essentially the average noise
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has been normalized so that its median value (essentially the average noise
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@ -949,7 +949,7 @@ For JT65 this expression evaluates to
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\begin_layout Standard
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\begin_layout Standard
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\begin_inset Formula
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\begin_inset Formula
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\[
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\[
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u\approx1\pm0.13+(0.19\pm0.06)\,y.
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u\approx1\pm0.13+(0.19\pm0.06)\, y.
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\]
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\]
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\end_inset
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\end_inset
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@ -1028,7 +1028,7 @@ For each received symbol, define the erasure probability as 1.3 times the
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a priori
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a priori
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\emph default
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\emph default
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symbol-error probability determined from soft-symbol information
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symbol-error probability determined from soft-symbol information
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\begin_inset Formula $\{p_{1}\textrm{-rank},\,p_{2}/p_{1}\}$
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\begin_inset Formula $\{p_{1}\textrm{-rank},\, p_{2}/p_{1}\}$
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\end_inset
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\end_inset
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.
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.
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