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update reference for Zlatko's paper in ACM TOMS
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‎SRC/cgesvdq.f

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@@ -289,14 +289,9 @@
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*..............................................................................
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* References
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* ==========
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* [1] Z. Drmac: A QR-preconditioned QR SVD method for computing the SVD
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* with high accuracy, TR-2016-HRZZ-9345-1,
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* Department of Mathematics, University of Zagreb.
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* Submitted to ACM TOMS.
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* [2] Z. Drmac: xGESVDQ: A software implementation of the QR-preconditioned
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* QR SVD method for computing the singular value decomposition
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* TR-2016-HRZZ-9345-2, Department of Mathematics,
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* University of Zagreb. Submitted to ACM TOMS.
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* [1] Zlatko Drmac, Algorithm 977: A QR-Preconditioned QR SVD Method for
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* Computing the SVD with High Accuracy. ACM Trans. Math. Softw.
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* 44(1): 11:1-11:30 (2017)
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*.......................................................................
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*"""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""
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*
@@ -783,7 +778,7 @@ SUBROUTINE CGESVDQ( JOBA, JOBP, JOBR, JOBU, JOBV, M, N, A, LDA,
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SCONDA = ONE / SQRT(RTMP)
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* For NR=N, SCONDA is an estimate of SQRT(||(R^* * R)^(-1)||_1),
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* N^(-1/4) * SCONDA <= ||R^(-1)||_2 <= N^(1/4) * SCONDA
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* See the references [1], [2] for more details.
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* See the reference [1] for more details.
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END IF
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*
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ENDIF

‎SRC/dgesvdq.f

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Original file line numberDiff line numberDiff line change
@@ -291,14 +291,9 @@
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*..............................................................................
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* References
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* ==========
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* [1] Z. Drmac: A QR-preconditioned QR SVD method for computing the SVD
295-
* with high accuracy, TR-2016-HRZZ-9345-1,
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* Department of Mathematics, University of Zagreb.
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* Submitted to ACM TOMS.
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* [2] Z. Drmac: xGESVDQ: A software implementation of the QR-preconditioned
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* QR SVD method for computing the singular value decomposition
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* TR-2016-HRZZ-9345-2, Department of Mathematics,
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* University of Zagreb. Submitted to ACM TOMS.
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* [1] Zlatko Drmac, Algorithm 977: A QR-Preconditioned QR SVD Method for
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* Computing the SVD with High Accuracy. ACM Trans. Math. Softw.
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* 44(1): 11:1-11:30 (2017)
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*.......................................................................
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*"""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""
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*
@@ -783,7 +778,7 @@ SUBROUTINE DGESVDQ( JOBA, JOBP, JOBR, JOBU, JOBV, M, N, A, LDA,
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SCONDA = ONE / SQRT(RTMP)
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* For NR=N, SCONDA is an estimate of SQRT(||(R^* * R)^(-1)||_1),
785780
* N^(-1/4) * SCONDA <= ||R^(-1)||_2 <= N^(1/4) * SCONDA
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* See the references [1], [2] for more details.
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* See the reference [1] for more details.
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END IF
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*
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ENDIF

‎SRC/sgesvdq.f

Lines changed: 4 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -291,14 +291,9 @@
291291
*..............................................................................
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* References
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* ==========
294-
* [1] Z. Drmac: A QR-preconditioned QR SVD method for computing the SVD
295-
* with high accuracy, TR-2016-HRZZ-9345-1,
296-
* Department of Mathematics, University of Zagreb.
297-
* Submitted to ACM TOMS.
298-
* [2] Z. Drmac: xGESVDQ: A software implementation of the QR-preconditioned
299-
* QR SVD method for computing the singular value decomposition
300-
* TR-2016-HRZZ-9345-2, Department of Mathematics,
301-
* University of Zagreb. Submitted to ACM TOMS.
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* [1] Zlatko Drmac, Algorithm 977: A QR-Preconditioned QR SVD Method for
295+
* Computing the SVD with High Accuracy. ACM Trans. Math. Softw.
296+
* 44(1): 11:1-11:30 (2017)
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*.......................................................................
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*"""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""
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*
@@ -783,7 +778,7 @@ SUBROUTINE SGESVDQ( JOBA, JOBP, JOBR, JOBU, JOBV, M, N, A, LDA,
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SCONDA = ONE / SQRT(RTMP)
784779
* For NR=N, SCONDA is an estimate of SQRT(||(R^* * R)^(-1)||_1),
785780
* N^(-1/4) * SCONDA <= ||R^(-1)||_2 <= N^(1/4) * SCONDA
786-
* See the references [1], [2] for more details.
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* See the reference [1] for more details.
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END IF
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*
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ENDIF

‎SRC/zgesvdq.f

Lines changed: 4 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -289,14 +289,9 @@
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*..............................................................................
290290
* References
291291
* ==========
292-
* [1] Z. Drmac: A QR-preconditioned QR SVD method for computing the SVD
293-
* with high accuracy, TR-2016-HRZZ-9345-1,
294-
* Department of Mathematics, University of Zagreb.
295-
* Submitted to ACM TOMS.
296-
* [2] Z. Drmac: xGESVDQ: A software implementation of the QR-preconditioned
297-
* QR SVD method for computing the singular value decomposition
298-
* TR-2016-HRZZ-9345-2, Department of Mathematics,
299-
* University of Zagreb. Submitted to ACM TOMS.
292+
* [1] Zlatko Drmac, Algorithm 977: A QR-Preconditioned QR SVD Method for
293+
* Computing the SVD with High Accuracy. ACM Trans. Math. Softw.
294+
* 44(1): 11:1-11:30 (2017)
300295
*.......................................................................
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*"""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""
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*
@@ -783,7 +778,7 @@ SUBROUTINE ZGESVDQ( JOBA, JOBP, JOBR, JOBU, JOBV, M, N, A, LDA,
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SCONDA = ONE / SQRT(RTMP)
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* For NR=N, SCONDA is an estimate of SQRT(||(R^* * R)^(-1)||_1),
785780
* N^(-1/4) * SCONDA <= ||R^(-1)||_2 <= N^(1/4) * SCONDA
786-
* See the references [1], [2] for more details.
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* See the reference [1] for more details.
787782
END IF
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*
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ENDIF

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