| 3951. |
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| 3952. |
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| 3953. |
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| 3954. |
- Sun, J. G.
(author)
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Condition number and backward error for the generalized singular value decomposition
- 2000
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In: Siam Journal on Matrix Analysis and Applications. ; 22:2, s. 323-341
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Journal article (peer-reviewed)abstract
- Let A, B be two matrices having the same number of columns, and let (A(T), B-T)(T) have full column rank. Certain normwise condition numbers for a finite generalized singular value (GSV) of the matrix pair {A, B} are defined, and explicit expressions of the condition numbers for a simple, nonzero GSV are derived. Moreover, a normwise backward error of {A, B} with respect to an approximate GSV and an associated approximate generalized singular vector group is also defined, and a computable formula of the backward error is obtained. The results are illustrated by numerical examples.
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| 3955. |
- Sun, J. G.
(author)
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Condition numbers of algebraic Riccati equations in the Frobenius norm
- 2002
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In: Linear Algebra and Its Applications. ; 350, s. 237-261
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Journal article (peer-reviewed)abstract
- Consider the continuous-time algebraic Riccati equation (CARE) and the discrete-time algebraic Riccati equation (DARE) which arise in linear control and system theory. It is known that appropriate assumptions on the coefficient matrices guarantee the existence and uniqueness of Hermitian positive semidefinite stabilizing solutions. In this note, we apply the theory of condition developed by Rice to define condition numbers of the CARE and DARE in the Frobenius norm, and derive explicit expressions of the condition numbers in a uniform manner. Both the complex case and real case are considered, and connections to certain existing condition numbers of the CARE and DARE are discussed. (C) 2002 Elsevier Science Inc. All rights reserved.
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| 3956. |
- Sun, J. G.
(author)
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Perturbation analysis of the matrix equation X = Q+A(H)((X)over-cap-C)(-1) A
- 2003
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In: Linear Algebra and Its Applications. ; 372, s. 33-51
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Journal article (peer-reviewed)abstract
- Consider the nonlinear matrix equation X=Q+A(H)((X) over cap - C)-(1)A, where Q is an n x n Hermitian positive definite matrix, C is an mn x mn Hermitian positive semidefinite matrix, A is an mn x n matrix, and (X) over cap is the m x m block diagonal matrix defined by (X) over cap = diag(X, X,..., X), in which X is an n x n matrix. This matrix equation is connected with certain interpolation problem. In this paper, perturbation bounds and condition numbers for the maximal solution are presented, and residual bounds for an approximate solution to the maximal solution are obtained. The results are illustrated by numerical examples. (C) 2003 Elsevier Inc. All rights reserved.
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| 3957. |
- Sun, J. G., et al.
(author)
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Perturbation analysis of the maximal solution of the matrix equation X+A* X-1 A = P. II
- 2003
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In: Linear Algebra and Its Applications. ; 362, s. 211-228
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Journal article (peer-reviewed)abstract
- Consider the nonlinear matrix equation X + A*X(-1)A = P, where A, P are n x n complex matrices with P Hermitian positive definite, and A* denotes the conjugate transpose of a matrix A. In this paper A sharper perturbation bound for the maximal solution to the matrix equation is derived, explicit expressions of the condition number for the maximal solution are obtained, and the backward error of an approximate solution to the maximal solution is evaluated by using the techniques developed in [Linear Algebra Appl. 259 (1997) 183; Linear Algebra Appl. 350 (2002) 237]. The, results are illustrated by using numerical examples. (C) 2002 Elsevier Science Inc. All rights reserved.
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| 3958. |
- Sundblad, Lars-Göran, et al.
(author)
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Fast, nondestructive measurement of frost hardiness in conifer seedlings by VIS+NIR spectroscopy
- 2001
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In: Tree Physiology. ; 21, s. 751–7-
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Journal article (peer-reviewed)abstract
- Frost hardiness development from mid-August to mid-November was evaluated in seedlings of three provenances of Norway spruce (Picea abies (L.) Karst.) and three provenances of Scots pine (Pinus sylvestris L.) raised at nurseries in north, central and south Sweden. Measurements of the visible + near infrared (VIS+NIR) spectra of shoots were made simultaneously with estimates of frost hardiness based on electrolyte leakage following artificial freezing. Nine physiological variables known to influence frost hardiness were measured throughout the experiment. Multivariate analysis showed that VIS+NIR spectra explained 69% and 72% of the variation in frost hardiness in Scots pine and Norway spruce, respectively. Stem lignification, dry weight fraction, and starch, glucose, fructose, galactose, sucrose, raffinose and stachyose concentrations together explained 80% and 85% of the variation in frost hardiness in Scots pine and Norway spruce, respectively when used as independent X variables in a partial least squares model. These physiological variables could be related to varying degrees with variation in the VIS+NIR spectra. We conclude that VIS+NIR spectroscopy provides a rapid nondestructive technique for measuring frost hardiness in conifer seedlings based on causal relationships between the spectra and the physiology of seedling frost hardiness.
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| 3959. |
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| 3960. |
- Sundgren, Stefan, et al.
(author)
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The effects of the auditor's professional qualification and the firm's financial health on depreciation in Finland
- 2004
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In: Accounting and Business Research. ; 34:2, s. 125-143
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Journal article (peer-reviewed)abstract
- This study examines the relationship in Finland between the firm's financial health and the depreciation policy for a sample with 1,610 firm-years of data for mainly non-public firms. We find a negative correlation between leverage and depreciation in relation to depreciable assets. This result is consistent with prior studies showing that firms with a higher leverage use income-increasing accounting methods. However, since accounting-based debt covenants are rare among the size class of firms studied, the correlation is likely to be driven by implicit contracting related factors. We also study whether the auditors' professional qualifications correlate with the depreciation policy. The results indicate that Big 5 audited firms depreciate their assets over somewhat shorter periods of time than non-Big 5 audited firms. This result is consistent with the notion that Big 5 auditors are more conservative, perhaps because they have more reputation capital at stake.
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