
A contribution to condition numbers of the multidimensional total least squares problem with linear equality constraint
This paper is devoted to condition numbers of the multidimensional total...
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Condition numbers of the mixed least squarestotal least squares problem: revisited
A new closed formula for the first order perturbation estimate of the mi...
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Condition numbers for the truncated total least squares problem and their estimations
In this paper, we present explicit expressions for the mixed and compone...
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Structured condition numbers for the total least squares problem with linear equality constraint and their statistical estimation
In this paper, we derive the mixed and componentwise condition numbers f...
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Structured condition number for multiple righthand side linear systems with parameterized quasiseparable coefficient matrix
In this paper, we consider the structured perturbation analysis for mult...
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On condition numbers of symmetric and nonsymmetric domain decomposition methods
Using oblique projections and angles between subspaces we write conditio...
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Probabilistic Condition Number Estimates for Real Polynomial Systems II: Structure and Smoothed Analysis
We consider the sensitivity of real zeros of polynomial systems with res...
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On the condition number of the total least squares problem with linear equality constraint
This paper is devoted to the condition number of the total least squares problem with linear equality constraint (TLSE). With novel techniques, closed formulae for the normwise, mixed and componentwise condition numbers of the TLSE problem are derived. Compact expressions and upper bounds for these condition numbers are also given to avoid the costly Kronecker productbased operations. Explicit condition number expressions and perturbation bound for the TLS problem can be recovered from our estimates. For random TLSE problems, numerical experiments illustrate the sharpness of the estimates based on normwise condition numbers, while for sparse and badly scaled matrices, the estimates based on mixed and componentwise condition numbers are much tighter.
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