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	Fix two small typos.
git-svn-id: svn+ssh://svn.code.sf.net/p/wsjt/wsjt/branches/wsjtx@6369 ab8295b8-cf94-4d9e-aec4-7959e3be5d79
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				| @ -246,7 +246,7 @@ The minimum Hamming distance of the JT65 code is | ||||
| \end_inset | ||||
| 
 | ||||
| , which means that any particular codeword differs from all other codewords | ||||
|  in at least 52 or the 63 symbol positions. | ||||
|  in at least 52 of the 63 symbol positions. | ||||
|   | ||||
| \end_layout | ||||
| 
 | ||||
| @ -849,7 +849,7 @@ The FT algorithm uses quality indices made available by a noncoherent 64-FSK | ||||
| \end_inset | ||||
| 
 | ||||
|  of the symbol's fractional power  | ||||
| \begin_inset Formula $p_{1,\,j}$ | ||||
| \begin_inset Formula $p_{1,\, j}$ | ||||
| \end_inset | ||||
| 
 | ||||
|  in a sorted list of  | ||||
| @ -919,7 +919,7 @@ t educated guesses to select symbols for erasure. | ||||
| , the soft distance between the received word and the codeword:  | ||||
| \begin_inset Formula  | ||||
| \begin{equation} | ||||
| d_{s}=\sum_{j=1}^{n}\alpha_{j}\,(1+p_{1,\,j}).\label{eq:soft_distance} | ||||
| d_{s}=\sum_{j=1}^{n}\alpha_{j}\,(1+p_{1,\, j}).\label{eq:soft_distance} | ||||
| \end{equation} | ||||
| 
 | ||||
| \end_inset | ||||
| @ -937,7 +937,7 @@ Here | ||||
| \end_inset | ||||
| 
 | ||||
|  if the received symbol and codeword symbol are different, and  | ||||
| \begin_inset Formula $p_{1,\,j}$ | ||||
| \begin_inset Formula $p_{1,\, j}$ | ||||
| \end_inset | ||||
| 
 | ||||
|  is the fractional power associated with received symbol  | ||||
| @ -981,7 +981,7 @@ In practice we find that | ||||
| \begin_layout Standard | ||||
| \begin_inset Formula  | ||||
| \begin{equation} | ||||
| u=\frac{1}{n}\sum_{j=1}^{n}S(c_{j},\,j).\label{eq:u-metric} | ||||
| u=\frac{1}{n}\sum_{j=1}^{n}S(c_{j},\, j).\label{eq:u-metric} | ||||
| \end{equation} | ||||
| 
 | ||||
| \end_inset | ||||
| @ -1014,7 +1014,7 @@ The correct JT65 codeword produces a value for | ||||
| 
 | ||||
|  bins containing noise only. | ||||
|  Thus, if the spectral array  | ||||
| \begin_inset Formula $S(i,\,j)$ | ||||
| \begin_inset Formula $S(i,\, j)$ | ||||
| \end_inset | ||||
| 
 | ||||
|  has been normalized so that the average value of the noise-only bins is | ||||
| @ -1263,7 +1263,7 @@ For each received symbol, define the erasure probability as 1.3 times the | ||||
| a priori | ||||
| \emph default | ||||
|  symbol-error probability determined from soft-symbol information  | ||||
| \begin_inset Formula $\{p_{1}\textrm{-rank},\,p_{2}/p_{1}\}$ | ||||
| \begin_inset Formula $\{p_{1}\textrm{-rank},\, p_{2}/p_{1}\}$ | ||||
| \end_inset | ||||
| 
 | ||||
| . | ||||
| @ -1595,7 +1595,7 @@ If | ||||
| \begin_inset Formula $u$ | ||||
| \end_inset | ||||
| 
 | ||||
|  is the largest found so far, presevre any previous value of  | ||||
|  is the largest found so far, preserve any previous value of  | ||||
| \begin_inset Formula $u_{1}$ | ||||
| \end_inset | ||||
| 
 | ||||
|  | ||||
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