Sparse Linear Parametric Modeling of Room Acoustics with Orthonormal Basis Functions

G. Vairetti, T. von Waterschoot, M. Moonen, M. Catrysse, Søren Holdt Jensen

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

5 Citations (Scopus)


Orthonormal Basis Function (OBF) models provide a stable and well-conditioned representation of a linear system. When used for the modeling of room acoustics, useful information about the true dynamics of the system can be introduced by a proper selection of a set of poles, which however appear non-linearly in the model. A novel method for selecting the poles is proposed, which bypass the non-linear problem by exploiting the concept of sparsity and by using convex optimization. The model obtained has a longer impulse response compared to the all-zero model with the same number of parameters, without introducing substantial error in the early response. The method also allows to increase the resolution in a specified frequency region, while still being able to approximate the spectral envelope in other regions.
Original languageEnglish
Title of host publicationSignal Processing Conference (EUSIPCO), 2014 Proceedings of the 22nd European
Number of pages5
Publication date2014
ISBN (Print)9780992862619
Publication statusPublished - 2014
EventEUSIPCO 2014 - Lisbon Congress Centre, Lisbon, Portugal
Duration: 1 Sep 20145 Sep 2014


ConferenceEUSIPCO 2014
LocationLisbon Congress Centre
SeriesProceedings of the European Signal Processing Conference

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