A few more minor tweaks to the text.

git-svn-id: svn+ssh://svn.code.sf.net/p/wsjt/wsjt/branches/wsjtx@6208 ab8295b8-cf94-4d9e-aec4-7959e3be5d79

lib/sfrsd2/sfrsd_paper/sfrsd.lyx

@@ -118,7 +118,7 @@ on with a Reed-Solomon code.
 
 , the number of message symbols conveyed by the codeword, and the number
  of possible values for each symbol in the codewords.
- The codeword length and the number of message symbols are specified using
+ The codeword length and the number of message symbols are specified with
  the notation 
 \begin_inset Formula $(n,k)$
 \end_inset
@@ -252,7 +252,11 @@ errors.
 \begin_inset Formula $s$
 \end_inset
 
- symbols are erased and the remaining (unerased) symbols contain 
+ symbols are erased and the remaining 
+\begin_inset Formula $n-s$
+\end_inset
+
+ symbols contain 
 \begin_inset Formula $e$
 \end_inset
 
@@ -296,7 +300,7 @@ errors-and-erasures
  decoder.
  The possibility of doing errors-and-erasures decoding lies at the heart
  of the FT algorithm.
- On that foundation we build a capability for using 
+ On that foundation we have built a capability for using 
 \begin_inset Quotes eld
 \end_inset
 
@@ -304,7 +308,7 @@ soft
 \begin_inset Quotes erd
 \end_inset
 
- information on symbol reliability.
+ information on symbol reliability, thereby producing a soft-decision decoder.
 \end_layout
 
 \begin_layout Section
@@ -319,7 +323,7 @@ Do I feel lucky?
 
 \begin_layout Standard
 The FT algorithm uses the estimated quality of received symbols to generate
- lists of symbols considered likely to be in error, thereby enabling reliable
+ lists of symbols considered likely to be in error, thus enabling reliable
  decoding of received words with more than 25 errors.
  As a specific example, consider a received JT65 word with 23 correct symbols
  and 40 errors.
@@ -559,8 +563,8 @@ Examples 1 and 2 show that a random strategy for selecting symbols to erase
 
  incorrect symbols, as before, but suppose we know that 10 symbols are significa
 ntly more reliable than the other 53.
- We might therefore protect the 10 most reliable symbols from erasure, and
- choose erasures from the smaller set of 
+ We might therefore protect the 10 most reliable symbols from erasure, selecting
+ erasures from the smaller set of 
 \begin_inset Formula $N=53$
 \end_inset
 
@@ -641,8 +645,8 @@ The FT decoding algorithm
 Example 3 shows how reliable information about symbol quality should make
  it possible to decode received frames having a large number of errors.
  In practice the number of errors in the received word is unknown, so we
- use a stochastic algorithm to assign a high erasure probability to low-quality
- symbols and a relatively low probability to high-quality symbols.
+ use a stochastic algorithm to assign high erasure probability to low-quality
+ symbols and relatively low probability to high-quality symbols.
  As illustrated by Example 3, a good choice of these probabilities can increase
  the chance of a successful decode by many orders of magnitude.
 \end_layout
@@ -651,8 +655,7 @@ Example 3 shows how reliable information about symbol quality should make
 The FT algorithm uses two quality indices made available by a noncoherent
  64-FSK demodulator.
  The demodulator identifies the most likely value for each symbol based
- on which of 64 frequency bins contains the the largest signal-plus-noise
- power.
+ on the largest signal-plus-noise power in 64 frequency bins.
  The fraction of total power in the two bins containing the largest and
  second-largest powers (denoted by 
 \begin_inset Formula $p_{1}$
@@ -829,7 +832,7 @@ 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
 
 .
@@ -931,6 +934,9 @@ Number of decodes vs.
 \begin_layout Itemize
 Probability of successful decode vs.
  Es/No or S/N in 2500 Hz BW
+\end_layout
+
+\begin_layout Standard
 \begin_inset Float figure
 wide false
 sideways false
@@ -940,6 +946,8 @@ status open
 \align center
 \begin_inset Graphics
 	filename fig_psuccess.pdf
+	lyxscale 120
+	scale 120
 
 \end_inset
 
@@ -952,8 +960,8 @@ status open
 \begin_layout Plain Layout
 Percentage of JT65 messages successfully decoded as a function of SNR in
  2.5 kHz bandwidth.
- Results are shown for the hard-decision Berlekamp-Massey (BM) and the Franke-Ta
-ylor (FT) decoding algorithms.
+ Results are shown for the hard-decision Berlekamp-Massey (BM) and the sofft-dec
+ision Franke-Taylor (FT) decoding algorithms.
 \end_layout
 
 \end_inset