By Ivan Markovsky
Data Approximation via Low-complexity types info the idea, algorithms, and purposes of established low-rank approximation. effective neighborhood optimization tools and potent suboptimal convex relaxations for Toeplitz, Hankel, and Sylvester based difficulties are offered. a lot of the textual content is dedicated to describing the purposes of the speculation together with: procedure and keep watch over thought; sign processing; machine algebra for approximate factorization and customary divisor computation; machine imaginative and prescient for photo deblurring and segmentation; laptop studying for info retrieval and clustering; bioinformatics for microarray facts research; chemometrics for multivariate calibration; and psychometrics for issue analysis.
Software implementation of the equipment is given, making the idea without delay acceptable in perform. All numerical examples are incorporated in demonstration documents giving hands-on adventure and routines and MATLAB® examples help in the assimilation of the theory.
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