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C Find next member of prediction error filter G(NP1).
10 SN=(0.D0,0.D0)
SD=(0.D0,0.D0)
C Find upper limit of sum.
JJ=M-N-1
DO 12 J=1,JJ
SN=SN-2.D0*PEF(J+N+1)*DCONJG(PER(J))
SD=SD+PEF(J+N+1)*DCONJG(PEF(J+N+1))+PER(J)*DCONJG(PER(J))
12 CONTINUE
G(NP1)=SN/SD
C If previous recursion number is zero, do not update prediction error
C filter coefficients.
IF(N.EQ.0) GO TO 13
C Update prediction error filter coefficients and store them in vector H(J).
DO 14 J=1,N
K=N-J+1
H(J)=G(J)+G(NP1)*DCONJG(G(K))
14 CONTINUE
C Put updated prediction error coefficients in G(J).
DO 15 J=1,N
G(J)=H(J)
15 CONTINUE
C Update forward prediction error sequence and store in H(K).
13 DO 16 J=1,JJ
K=J+NP1
H(K)=PEF(K)+G(NP1)*PER(J)
16 CONTINUE
C Update backward prediction error sequence and store in O(J).
DO 17 J=1,JJ
O(J)=PER(J)+DCONJG(G(NP1))*PEF(J+NP1)
17 CONTINUE
C Put updated forward and backward prediction error sequences
C in PEF(K) and PER(J),respectively.
DO 18 J=1,JJ
K=J+NP1
PEF(K)=H(K)
PER(J)=O(J)
18
CONTINUE
RETURN
END
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