9781611977943 - numerical methods for least squares problem di åke björck (author) (16 risultati)
Lingua: Inglese
Editore: SIAM - Society for Industrial and Applied Mathematics, 2024
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Lingua: Inglese
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Condizione: New. 2024. 2nd Edition. paperback. . . . . .
Lingua: Inglese
Editore: SIAM - Society for Industrial and Applied Mathematics, 2024
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Lingua: Inglese
Editore: Society for Industrial and Applied Mathematics,U.S., US, 2024
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Paperback. Condizione: New. Second Edition. The method of least squares, discovered by Gauss in 1795, is a principal tool for reducing the influence of errors when fitting a mathematical model to given observations. Applications arise in a great number of areas in sciences and engineering. The increased use of automatic data cap…turing frequently leads to large-scale least squares problems. Such problems can be solved by using recent developments in preconditioned iterative methods and in sparse QR factorization. The first edition of Numerical Methods for Least Squares Problem was the leading reference on least squares problems for many years. The updated second edition stands out compared to other books on the topic because:it provides an in-depth and up to date treatment of direct and iterative methods for solving different types of least squares problems and for computing the singular value decomposition;covers generalized, constrained, and nonlinear least squares problems as well as partial least squares and regularization methods for discrete ill-posed problems; andcontains a bibliography with more than 1100 historical and recent references, providing a unique survey of past and present research in the field.
Lingua: Inglese
Editore: Society for Industrial & Applied Mathematics,U.S., New York, 2024
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Paperback. Condizione: new. Paperback. The method of least squares, discovered by Gauss in 1795, is a principal tool for reducing the influence of errors when fitting a mathematical model to given observations. Applications arise in a great number of areas in sciences and engineering. The increased use of automatic data capturin…g frequently leads to large-scale least squares problems. Such problems can be solved by using recent developments in preconditioned iterative methods and in sparse QR factorization. The first edition of Numerical Methods for Least Squares Problem was the leading reference on least squares problems for many years. The updated second edition stands out compared to other books on the topic because:it provides an in-depth and up to date treatment of direct and iterative methods for solving different types of least squares problems and for computing the singular value decomposition;covers generalized, constrained, and nonlinear least squares problems as well as partial least squares and regularization methods for discrete ill-posed problems; andcontains a bibliography with more than 1100 historical and recent references, providing a unique survey of past and present research in the field. The method of least squares, discovered by Gauss in 1795, is a principal tool for reducing the influence of errors when fitting a mathematical model to given observations. Applications arise in a great number of areas in sciences and engineering. The increased use of automatic data capturing frequently leads to large-scale least squares problems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: SIAM - Society for Industrial and Applied Mathematics, 2024
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Lingua: Inglese
Editore: SIAM - Society for Industrial and Applied Mathematics, 2024
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Lingua: Inglese
Editore: SIAM - Society for Industrial and Applied Mathematics, 2024
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Editore: Society for Industrial and Applied Mathematics,U.S., US, 2024
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Paperback. Condizione: New. Second Edition. The method of least squares, discovered by Gauss in 1795, is a principal tool for reducing the influence of errors when fitting a mathematical model to given observations. Applications arise in a great number of areas in sciences and engineering. The increased use of automatic data cap…turing frequently leads to large-scale least squares problems. Such problems can be solved by using recent developments in preconditioned iterative methods and in sparse QR factorization. The first edition of Numerical Methods for Least Squares Problem was the leading reference on least squares problems for many years. The updated second edition stands out compared to other books on the topic because:it provides an in-depth and up to date treatment of direct and iterative methods for solving different types of least squares problems and for computing the singular value decomposition;covers generalized, constrained, and nonlinear least squares problems as well as partial least squares and regularization methods for discrete ill-posed problems; andcontains a bibliography with more than 1100 historical and recent references, providing a unique survey of past and present research in the field.
Lingua: Inglese
Editore: Society for Industrial & Applied Mathematics,U.S., New York, 2024
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Paperback. Condizione: new. Paperback. The method of least squares, discovered by Gauss in 1795, is a principal tool for reducing the influence of errors when fitting a mathematical model to given observations. Applications arise in a great number of areas in sciences and engineering. The increased use of automatic data capturin…g frequently leads to large-scale least squares problems. Such problems can be solved by using recent developments in preconditioned iterative methods and in sparse QR factorization. The first edition of Numerical Methods for Least Squares Problem was the leading reference on least squares problems for many years. The updated second edition stands out compared to other books on the topic because:it provides an in-depth and up to date treatment of direct and iterative methods for solving different types of least squares problems and for computing the singular value decomposition;covers generalized, constrained, and nonlinear least squares problems as well as partial least squares and regularization methods for discrete ill-posed problems; andcontains a bibliography with more than 1100 historical and recent references, providing a unique survey of past and present research in the field. The method of least squares, discovered by Gauss in 1795, is a principal tool for reducing the influence of errors when fitting a mathematical model to given observations. Applications arise in a great number of areas in sciences and engineering. The increased use of automatic data capturing frequently leads to large-scale least squares problems. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Lingua: Inglese
Editore: SIAM - Society for Industrial and Applied Mathematics, 2024
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paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
