# Total least squares

## Papers overview

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Highly Cited

2011

Highly Cited

2011

- IEEE Transactions on Signal Processing
- 2011

Solving linear regression problems based on the total least-squares (TLS) criterion has well-documented merits in variousâ€¦Â (More)

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Highly Cited

2006

Highly Cited

2006

- IEEE Transactions on Image Processing
- 2006

In this paper, we present a method for removing noise from digital images corrupted with additive, multiplicative, and mixedâ€¦Â (More)

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Highly Cited

2002

Highly Cited

2002

- Computational Statistics & Data Analysis
- 2002

The total least squares method is a numerical linear algebra tool for finding approximate solutions to overdetermined systems ofâ€¦Â (More)

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2002

2002

- 2002

The standard approaches to solving overdetermined linear systems Ax â‰ˆ b construct minimal corrections to the vector b and/or theâ€¦Â (More)

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Highly Cited

1999

Highly Cited

1999

- SIAM J. Matrix Analysis Applications
- 1999

Discretizations of inverse problems lead to systems of linear equations with a highly ill-conditioned coefficient matrix, and inâ€¦Â (More)

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Highly Cited

1997

Highly Cited

1997

- SIAM J. Scientific Computing
- 1997

The total least squares (TLS) method is a successful method for noise reduction in linear least squares problems in a number ofâ€¦Â (More)

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Highly Cited

1995

Highly Cited

1995

- IEEE Trans. Image Processing
- 1995

In this paper, the problem of restoring an image distorted by a linear space-invariant (LSI) point-spread function (PSF) that isâ€¦Â (More)

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Highly Cited

1994

Highly Cited

1994

- IEEE Trans. Signal Processing
- 1994

Structured rank-deficient matrices arise in many applications in signal processing, system identification, and control theory. Weâ€¦Â (More)

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Highly Cited

1987

Highly Cited

1987

- IEEE Trans. Acoustics, Speech, and Signalâ€¦
- 1987

The resolution of the estimated closely spaced frequencies of the multiple sinusoids degrades as the signal-to-noise ratio (SNRâ€¦Â (More)

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Highly Cited

1984

Highly Cited

1984

- 1984

Classical least squares regression consists of minimizing the sum of the squared residuals. Many authors have produced moreâ€¦Â (More)

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