Ir al contenido

Documat


Software for weighted structured low-rank approximation

  • Autores: I. Markovsky, Konstantin Usevich
  • Localización: Journal of computational and applied mathematics, ISSN 0377-0427, Vol. 256, Nº 1, 2014, págs. 278-292
  • Idioma: inglés
  • DOI: 10.1016/j.cam.2013.07.048
  • Texto completo no disponible (Saber más ...)
  • Resumen
    • A software package is presented that computes locally optimal solutions to low-rank approximation problems with the following features:

      . mosaic Hankel structure constraint on the approximating matrix, . weighted 2-norm approximation criterion, . fixed elements in the approximating matrix, . missing elements in the data matrix, and . linear constraints on an approximating matrix�fs left kernel basis.

      It implements a variable projection type algorithm and allows the user to choose standard local optimization methods for the solution of the parameter optimization problem. For an m �~ n data matrix, with n > m, the computational complexity of the cost function and derivative evaluation is O(m2n). The package is suitable for applications with n �â m.

      In statistical estimation and data modeling . the main application areas of the package . n �â m corresponds to modeling of large amount of data by a low-complexity model.

      Performance results on benchmark system identification problems from the database DAISY and approximate common divisor problems are presented.


Fundación Dialnet

Mi Documat

Opciones de artículo

Opciones de compartir

Opciones de entorno