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https://github.com/saitohirga/WSJT-X.git
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a51c5c4251
As at ^/branches/wsjtx_exp@5271 git-svn-id: svn+ssh://svn.code.sf.net/p/wsjt/wsjt/branches/wsjtx@5272 ab8295b8-cf94-4d9e-aec4-7959e3be5d79
57 lines
2.7 KiB
Fortran
57 lines
2.7 KiB
Fortran
subroutine getmet4(mettab,ndelta)
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! Return appropriate metric table for soft-decision convolutional decoder.
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! Metric table (RxSymbol,TxSymbol)
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! integer mettab(0:255,0:1)
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integer mettab(-128:127,0:1)
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real*4 xx0(0:255)
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data xx0/ &
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1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, &
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1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, &
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1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, &
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1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, &
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1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, &
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1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, &
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0.988, 1.000, 0.991, 0.993, 1.000, 0.995, 1.000, 0.991, &
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1.000, 0.991, 0.992, 0.991, 0.990, 0.990, 0.992, 0.996, &
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0.990, 0.994, 0.993, 0.991, 0.992, 0.989, 0.991, 0.987, &
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0.985, 0.989, 0.984, 0.983, 0.979, 0.977, 0.971, 0.975, &
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0.974, 0.970, 0.970, 0.970, 0.967, 0.962, 0.960, 0.957, &
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0.956, 0.953, 0.942, 0.946, 0.937, 0.933, 0.929, 0.920, &
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0.917, 0.911, 0.903, 0.895, 0.884, 0.877, 0.869, 0.858, &
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0.846, 0.834, 0.821, 0.806, 0.790, 0.775, 0.755, 0.737, &
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0.713, 0.691, 0.667, 0.640, 0.612, 0.581, 0.548, 0.510, &
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0.472, 0.425, 0.378, 0.328, 0.274, 0.212, 0.146, 0.075, &
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0.000,-0.079,-0.163,-0.249,-0.338,-0.425,-0.514,-0.606, &
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-0.706,-0.796,-0.895,-0.987,-1.084,-1.181,-1.280,-1.376, &
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-1.473,-1.587,-1.678,-1.790,-1.882,-1.992,-2.096,-2.201, &
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-2.301,-2.411,-2.531,-2.608,-2.690,-2.829,-2.939,-3.058, &
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-3.164,-3.212,-3.377,-3.463,-3.550,-3.768,-3.677,-3.975, &
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-4.062,-4.098,-4.186,-4.261,-4.472,-4.621,-4.623,-4.608, &
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-4.822,-4.870,-4.652,-4.954,-5.108,-5.377,-5.544,-5.995, &
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-5.632,-5.826,-6.304,-6.002,-6.559,-6.369,-6.658,-7.016, &
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-6.184,-7.332,-6.534,-6.152,-6.113,-6.288,-6.426,-6.313, &
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-9.966,-6.371,-9.966,-7.055,-9.966,-6.629,-6.313,-9.966, &
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-5.858,-9.966,-9.966,-9.966,-9.966,-9.966,-9.966,-9.966, &
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-9.966,-9.966,-9.966,-9.966,-9.966,-9.966,-9.966,-9.966, &
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-9.966,-9.966,-9.966,-9.966,-9.966,-9.966,-9.966,-9.966, &
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-9.966,-9.966,-9.966,-9.966,-9.966,-9.966,-9.966,-9.966, &
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-9.966,-9.966,-9.966,-9.966,-9.966,-9.966,-9.966,-9.966, &
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-9.966,-9.966,-9.966,-9.966,-9.966,-9.966,-9.966,-9.966/
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save
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bias=0.5
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scale=50
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ndelta=nint(3.4*scale)
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do i=0,255
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xx=xx0(i)
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if(i.ge.160) xx=xx0(160) - (i-160)*6.822/65.3
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mettab(i-128,0)=nint(scale*(xx-bias))
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if(i.ge.1) mettab(128-i,1)=mettab(i-128,0)
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enddo
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mettab(-128,1)=mettab(-127,1)
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return
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end subroutine getmet4
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