Parameterized source separation for delayed spectroscopic signals

Abstract This paper addresses delayed (also known as anechoic) source separation when the source shape can be modeled by parameterized waveforms. An Alternating Least Squares (ALS) scheme is proposed to estimate the source shape parameters in a first step and both the mixing coefficients and the delays in a second step. For the challenging delay parameter estimation step, we adopt a strategy inspired by greedy algorithms. For highly correlated sources, the separation becomes ambiguous, and a second algorithm is proposed: a regularization term is added to favor slow delay evolution within each source. Results on synthetic and real data demonstrate the effectiveness of both algorithms compared to state-of-the-art methods for highly correlated Gaussian waveforms.

• Publication year

  2019

• Venue

  Signal Processing

• Publication date

  2019-05-01

• Fields of study

  Physics, Computer Science, Engineering

• Identifiers
  DOI 10.1016/J.SIGPRO.2018.12.015
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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