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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    BIT 39 (1999), S. 757-779 
    ISSN: 1572-9125
    Keywords: Overdetermined linear systems ; rank reduction ; Hankel structure ; Toeplitz structure ; structured total least norm ; total least squares ; 1-norm ; 2-norm ; singular value decomposition
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The structure preserving rank reduction problem arises in many important applications. The singular value decomposition (SVD), while giving the closest low rank approximation to a given matrix in matrix L 2 norm and Frobenius norm, may not be appropriate for these applications since it does not preserve the given structure. We present a new method for structure preserving low rank approximation of a matrix, which is based on Structured Total Least Norm (STLN). The STLN is an efficient method for obtaining an approximate solution to an overdetermined linear system AX ≈ B, preserving the given linear structure in the perturbation [E F] such that (A + E)X = B + F. The approximate solution can be obtained to minimize the perturbation [E F] in the L p norm, where p = 1, 2, or ∞. An algorithm is described for Hankel structure preserving low rank approximation using STLN with L p norm. Computational results are presented, which show performances of the STLN based method for L 1 and L 2 norms for reduced rank approximation for Hankel matrices.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Chichester [u.a.] : Wiley-Blackwell
    International Journal for Numerical Methods in Engineering 41 (1998), S. 1133-1151 
    ISSN: 0029-5981
    Keywords: flow control ; numerical solution of Navier-Stokes equation ; Karhunen-Loève Galerkin procedure ; Engineering ; Numerical Methods and Modeling
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Mathematics , Technology
    Notes: A new method of solving the Navier-Stokes equations efficiently by reducing their number of modes is proposed in the present paper. It is based on the Karhunen-Loève decomposition which is a technique of obtaining empirical eigenfunctions from the experimental or numerical data of a system. Employing these empirical eigenfunctions as basis functions of a Galerkin procedure, one can a priori limit the function space considered to the smallest linear subspace that is sufficient to describe the observed phenomena, and consequently reduce the Navier-Stokes equation defined on a complicated geometry to a set of ordinary differential equations with a minimum degree of freedom. The present algorithm is well suited for the problems of flow control or optimization, where one has to compute the flow field repeatedly using the Navier-Stokes equation but one can also estimate the approximate solution space of the flow field based on the range of control variables. The low-dimensional dynamic model of viscous fluid flow derived by the present method is shown to produce accurate flow fields at a drastically reduced computational cost when compared with the finite difference solution of the Navier-Stokes equation. © 1998 John Wiley & Sons, Ltd.
    Additional Material: 8 Ill.
    Type of Medium: Electronic Resource
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