Saved in:
Bibliographic Details
Main Authors: Schlecht, Sebastian J., Habets, Emanuël A. P.
Format: Preprint
Published: 2019
Subjects:
Online Access:https://arxiv.org/abs/1901.08865
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866916533523972096
author Schlecht, Sebastian J.
Habets, Emanuël A. P.
author_facet Schlecht, Sebastian J.
Habets, Emanuël A. P.
contents Feedback delay networks (FDNs) belong to a general class of recursive filters which are widely used in sound synthesis and physical modeling applications. We present a numerical technique to compute the modal decomposition of the FDN transfer function. The proposed pole finding algorithm is based on the Ehrlich-Aberth iteration for matrix polynomials and has improved computational performance of up to three orders of magnitude compared to a scalar polynomial root finder. We demonstrate how explicit knowledge of the FDN's modal behavior facilitates analysis and improvements for artificial reverberation. The statistical distribution of mode frequency and residue magnitudes demonstrate that relatively few modes contribute a large portion of impulse response energy.
format Preprint
id arxiv_https___arxiv_org_abs_1901_08865
institution arXiv
publishDate 2019
record_format arxiv
spellingShingle Modal Decomposition of Feedback Delay Networks
Schlecht, Sebastian J.
Habets, Emanuël A. P.
Systems and Control
Feedback delay networks (FDNs) belong to a general class of recursive filters which are widely used in sound synthesis and physical modeling applications. We present a numerical technique to compute the modal decomposition of the FDN transfer function. The proposed pole finding algorithm is based on the Ehrlich-Aberth iteration for matrix polynomials and has improved computational performance of up to three orders of magnitude compared to a scalar polynomial root finder. We demonstrate how explicit knowledge of the FDN's modal behavior facilitates analysis and improvements for artificial reverberation. The statistical distribution of mode frequency and residue magnitudes demonstrate that relatively few modes contribute a large portion of impulse response energy.
title Modal Decomposition of Feedback Delay Networks
topic Systems and Control
url https://arxiv.org/abs/1901.08865