Publication detail

A new generalized projection and its application to acceleration of audio declipping

RAJMIC, P. ZÁVIŠKA, P. VESELÝ, V. MOKRÝ, O.

Original Title

A new generalized projection and its application to acceleration of audio declipping

Type

journal article in Web of Science

Language

English

Original Abstract

In convex optimization, it is often inevitable to work with projectors onto convex sets composed with a linear operator. Such a need arises from both the theory and applications, with signal processing being a prominent and broad field where convex optimization has been used recently. In this article, a novel projector is presented, which generalizes previous results in that it admits to work with a broader family of linear transforms when compared with the state of the art but, on the other hand, it is limited to box-type convex sets in the transformed domain. The new projector is described by an explicit formula, which makes it simple to implement and requires a low computational cost. The projector is interpreted within the framework of the so-called proximal splitting theory. The convenience of the new projector is demonstrated on an example from signal processing, where it was possible to speed up the convergence of a signal declipping algorithm by a factor of more than two.

Keywords

projection; optimization; generalization; box constraints; declipping; desaturation; proximal splitting; sparsity

Authors

RAJMIC, P.; ZÁVIŠKA, P.; VESELÝ, V.; MOKRÝ, O.

Released

19. 9. 2019

Publisher

MDPI

Location

Basel

ISBN

2075-1680

Periodical

Axioms

Year of study

8

Number

3

State

Swiss Confederation

Pages from

1

Pages to

20

Pages count

20

URL

Full text in the Digital Library

BibTex

@article{BUT158565,
  author="Pavel {Rajmic} and Pavel {Záviška} and Vítězslav {Veselý} and Ondřej {Mokrý}",
  title="A new generalized projection and its application to acceleration of audio declipping",
  journal="Axioms",
  year="2019",
  volume="8",
  number="3",
  pages="1--20",
  doi="10.3390/axioms8030105",
  issn="2075-1680",
  url="https://www.mdpi.com/2075-1680/8/3/105"
}