Resumen de Software for weighted structured low-rank approximation

I. Markovsky, Konstantin Usevich

• 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.