Least-squares estimation of sound source directivity using convex selector of a better solution

    Research output: Contribution to journalArticle

    8 Citations (Scopus)

    Abstract

    Many acoustical simulation methods have been studied to investigate acoustical phenomena. Modeling of the directivity pattern of a sound source is also important for obtaining realistic simulation results. However, there has been little research on this. Although there has been research on sound source identification, the results might not be in a suitable form for numerical simulation. In this paper, a method for modeling a sound source from measured data is proposed. It utilizes the sum of monopoles as the physical model, and the modeling is achieved by estimating the model parameters. The estimation method is formulated as a convex optimization problem by assuming the smoothness of a solution and the sparseness of parameters. Moreover, an algorithm based on the alternating direction method of multipliers (ADMM) for solving the problem is derived. The validity of the method is evaluated using simulated data, and the modeling result for an actual loudspeaker is shown.

    Original languageEnglish
    Pages (from-to)128-136
    Number of pages9
    JournalAcoustical Science and Technology
    Volume38
    Issue number3
    DOIs
    Publication statusPublished - 2017

    Fingerprint

    selectors
    directivity
    acoustics
    simulation
    loudspeakers
    multipliers
    monopoles
    estimating
    optimization

    Keywords

    • Alternating direction method of multipliers (ADMM)
    • Convex optimization
    • Inverse problems
    • Least-squares method
    • Sparse approximation

    ASJC Scopus subject areas

    • Acoustics and Ultrasonics

    Cite this

    Least-squares estimation of sound source directivity using convex selector of a better solution. / Tamura, Yuki; Yatabe, Kohei; Oikawa, Yasuhiro.

    In: Acoustical Science and Technology, Vol. 38, No. 3, 2017, p. 128-136.

    Research output: Contribution to journalArticle

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