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T. Chan

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • eess.SP2
  • cs.SD1
  • eess.AS1
same name
  • T. Chan — 18 papers, h 21
  • T. Chan — 17 papers, h 9
  • T. Chan — 3 papers, h 63
  • T. Chan — 2 papers, h 13
  • T. Chan — 1 paper, h 7
  • T. Chan — 1 paper, h 13

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedPolar n-Complex and n-Bicomplex Singular Value Decomposition and Principal Component Pursuit

31 citations · 62 across the 4 of their papers we have counts for

collaborators

4 papers

eess.SP2018★ 23 cited

Complex and Quaternionic Principal Component Pursuit and Its Application to Audio Separation

Tak-Shing T. Chan, Yi-Hsuan Yang

Recently, the principal component pursuit has received increasing attention in signal processing research ranging from source separation to video surveillance. So far, all existing…

eess.AS2018★ 8 cited

Informed Group-Sparse Representation for Singing Voice Separation

Tak-Shing T. Chan, Yi-Hsuan Yang

Singing voice separation attempts to separate the vocal and instrumental parts of a music recording, which is a fundamental problem in music information retrieval. Recent work on s…

eess.SP2018★ 31 cited

Polar n-Complex and n-Bicomplex Singular Value Decomposition and Principal Component Pursuit

Tak-Shing T. Chan, Yi-Hsuan Yang

Informed by recent work on tensor singular value decomposition and circulant algebra matrices, this paper presents a new theoretical bridge that unifies the hypercomplex and tensor…

cs.SD2017

Music Signal Processing Using Vector Product Neural Networks

Z. C. Fan, T. S. Chan, Y. H. Yang +1

We propose a novel neural network model for music signal processing using vector product neurons and dimensionality transformations. Here, the inputs are first mapped from real val…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.