@inproceedings{7f6921682b674caeae36faf96f1cf615,

title = "Sparse Linear Parametric Modeling of Room Acoustics with Orthonormal Basis Functions",

abstract = "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.",

author = "G. Vairetti and {von Waterschoot}, T. and M. Moonen and M. Catrysse and Jensen, {S{\o}ren Holdt}",

year = "2014",

language = "English",

isbn = "9780992862619",

series = "Proceedings of the European Signal Processing Conference",

publisher = "IEEE",

pages = "1--5",

booktitle = "Signal Processing Conference (EUSIPCO), 2014 Proceedings of the 22nd European",

address = "United States",

note = "null ; Conference date: 01-09-2014 Through 05-09-2014",

}