CANDECOMP/PARAFAC decomposition based multi-dimensional nonuniform harmonic retrieval

Fuxi Wen, Wei Liu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Two CANDECOMP/PARAFAC decomposition based multi-dimensional nonuniform harmonic retrieval algorithms are derived, which are referred to as search efficient Tensor-MUSIC (SE-T-MUSIC) and generalized Tensor-ESPRIT (G-T-ESPRIT). Comparing with the conventional Tensor-MUSIC algorithm, SE-T-MUSIC reduces the computational complexity significantly in terms of the number of searching grids. On the other hand, G-T-ESPRIT is a search-free polynomial rooting based algorithm. It is a R-dimensional generalization of the conventional generalized ESPRIT approach and multidimensional optimization is not required. Furthermore, a CP decomposition based combinatorial search method is proposed to associate the estimated frequencies over R dimensions.

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE International Conference on Digital Signal Processing, DSP 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages172-176
Number of pages5
ISBN (Electronic)9781509041657
DOIs
Publication statusPublished - Mar 2017
Event2016 IEEE International Conference on Digital Signal Processing, DSP 2016 - Beijing, China
Duration: 16 Oct 201618 Oct 2016

Publication series

NameInternational Conference on Digital Signal Processing, DSP
Volume0

Conference

Conference2016 IEEE International Conference on Digital Signal Processing, DSP 2016
Country/TerritoryChina
CityBeijing
Period16/10/1618/10/16

Keywords

  • CP decomposition
  • Generalized Tensor-ESPRIT
  • multi-dimensional nonuniform harmonic retrieval (HR)
  • rank reduction
  • Searching efficient Tensor-MUSIC

ASJC Scopus subject areas

  • Signal Processing

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