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  • 1
    Book
    Book
    Philadelphia, PA :SIAM,
    Title: Solving least squares problems; 15
    Author: Lawson, Charles L.
    Contributer: Hanson, Richard J.
    Publisher: Philadelphia, PA :SIAM,
    Year of publication: 1995
    Pages: 337 S.
    Series Statement: Classics in applied mathematics 15
    Type of Medium: Book
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Book
    Book
    Englewood Cliffs, NJ :Prentice-Hall,
    Title: Solving least squares problems
    Author: Lawson, Charles L.
    Contributer: Hanson, Richard J.
    Publisher: Englewood Cliffs, NJ :Prentice-Hall,
    Year of publication: 1974
    Pages: 340 S.
    Type of Medium: Book
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Numerische Mathematik 24 (1975), S. 291-307 
    ISSN: 0945-3245
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract A general procedure is presented for numerically solving linear Fredholm integral equations of the first kind. The approximate solution is expressed as a continuous piecewise linear (spline) function. The method involves collocation followed by the solution of an appropriately scaled stabilized linear algebraic system. The procedure may be used iteratively to improve the accuracy of the approximate solution. Several numerical examples are given.
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical programming 21 (1981), S. 98-118 
    ISSN: 1436-4646
    Keywords: Linear Least Squares ; Equality Constraints ; Inequality Constraints ; Non-negativity Constraints
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract We present a new algorithm for solving a linear least squares problem with linear constraints. These are equality constraint equations and nonnegativity constraints on selected variables. This problem, while appearing to be quite special, is the core problem arising in the solution of the general linearly constrained linear least squares problem. The reduction process of the general problem to the core problem can be done in many ways. We discuss three such techniques. The method employed for solving the core problem is based on combining the equality constraints with differentially weighted least squares equations to form an augmented least squares system. This weighted least squares system, which is equivalent to a penalty function method, is solved with nonnegativity constraints on selected variables. Three types of examples are presented that illustrate applications of the algorithm. The first is rank deficient, constrained least squares curve fitting. The second is concerned with solving linear systems of algebraic equations with Hilbert matrices and bounds on the variables. The third illustrates a constrained curve fitting problem with inconsistent inequality constraints.
    Type of Medium: Electronic Resource
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