Signal processing in dual domain by adaptive projected subgradient method

Masahiro Yukawa, Konstantinos Slavakis, Isao Yamada.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

The goal of this paper is to establish a novel signal processing paradigm that enables us to find a point meeting time-variable specifications in dual domain (e.g., time and frequency domains) simultaneously. For this purpose, we define a new problem which we call adaptive split feasibility problem (ASFP). In the ASFP formulation, we have (i) a priori knowledge based convex constraints in the Euclidean spaces RN and RM and (ii) data-dependent convex sets in RN and RM; the latter are obtained in a sequential fashion. Roughly speaking, the problem is to find a common point of all the sets defined on RN such that its image under a given linear transformation is a common point of all the sets defined on RM, if such a point exists. We prove that the adaptive projected subgradient method (APSM) deals with the ASFP by employing (i) a projected gradient operator with respect to (w.r.t.) a 'fixed' proximity function reflecting the convex constraints and (ii) a subgradient projection w.r.t. 'time-varying' objective functions reflecting the data-dependent sets. The resulting algorithm requires no unwanted operations such as matrix inversion, therefore it is suitable for realtime implementation. A convergence analysis is presented and verified by numerical examples.

Original languageEnglish
Title of host publicationDSP 2009: 16th International Conference on Digital Signal Processing, Proceedings
DOIs
Publication statusPublished - 2009
Externally publishedYes
EventDSP 2009:16th International Conference on Digital Signal Processing - Santorini, Greece
Duration: 2009 Jul 52009 Jul 7

Other

OtherDSP 2009:16th International Conference on Digital Signal Processing
CountryGreece
CitySantorini
Period09/7/509/7/7

Fingerprint

Signal processing
Linear transformations
Specifications

Keywords

  • Adaptive projected subgradient method
  • Convex feasibility problem
  • Projected gradient
  • Split feasibility problem

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing

Cite this

Yukawa, M., Slavakis, K., & Yamada., I. (2009). Signal processing in dual domain by adaptive projected subgradient method. In DSP 2009: 16th International Conference on Digital Signal Processing, Proceedings [5201250] https://doi.org/10.1109/ICDSP.2009.5201250

Signal processing in dual domain by adaptive projected subgradient method. / Yukawa, Masahiro; Slavakis, Konstantinos; Yamada., Isao.

DSP 2009: 16th International Conference on Digital Signal Processing, Proceedings. 2009. 5201250.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Yukawa, M, Slavakis, K & Yamada., I 2009, Signal processing in dual domain by adaptive projected subgradient method. in DSP 2009: 16th International Conference on Digital Signal Processing, Proceedings., 5201250, DSP 2009:16th International Conference on Digital Signal Processing, Santorini, Greece, 09/7/5. https://doi.org/10.1109/ICDSP.2009.5201250
Yukawa M, Slavakis K, Yamada. I. Signal processing in dual domain by adaptive projected subgradient method. In DSP 2009: 16th International Conference on Digital Signal Processing, Proceedings. 2009. 5201250 https://doi.org/10.1109/ICDSP.2009.5201250
Yukawa, Masahiro ; Slavakis, Konstantinos ; Yamada., Isao. / Signal processing in dual domain by adaptive projected subgradient method. DSP 2009: 16th International Conference on Digital Signal Processing, Proceedings. 2009.
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