Title
Embedded-Optimization-Based Loudspeaker Precompensation Using a Hammerstein Loudspeaker Model
Abstract
This paper presents an embedded-optimization-based loudspeaker precompensation algorithm using a Hammerstein loudspeaker model, i.e. a cascade of a memoryless nonlinearity and a linear finite impulse response filter. The loudspeaker precompensation consists in a per-frame signal optimization. In order to minimize the perceptible distortion incurred in the loudspeaker, a psychoacoustically motivated optimization criterion is proposed. The resulting per-frame signal optimization problems are solved efficiently using first-order optimization methods. Depending on the invertibility and the smoothness of the memoryless nonlinearity, different first-order optimization methods are proposed and their convergence properties are analyzed. Objective evaluation experiments using synthetic loudspeaker models and real loudspeakers show that the proposed loudspeaker precompensation algorithm provides a significant audio quality improvement, especially so at high playback levels.
Year
DOI
Venue
2014
10.1109/TASLP.2014.2344862
Audio, Speech, and Language Processing, IEEE/ACM Transactions  
Keywords
Field
DocType
FIR filters,loudspeakers,optimisation,Hammerstein loudspeaker model,audio quality improvement,convergence properties,embedded-optimization-based loudspeaker precompensation algorithm,first-order optimization methods,linear finite impulse response filter,memoryless nonlinearity,per-frame signal optimization problems,perceptible distortion,psychoacoustic motivated optimization criterion,real loudspeaker model,synthetic loudspeaker models,Embedded optimization,gradient optimization,hammerstein model,loudspeaker precompensation,sound perception
Convergence (routing),Nonlinear system,Control theory,Computer science,Sound quality,Speech recognition,Cascade,Acoustics,Finite impulse response,Loudspeaker,Optimization problem,Distortion
Journal
Volume
Issue
ISSN
22
11
2329-9290
Citations 
PageRank 
References 
3
0.37
7
Authors
4
Name
Order
Citations
PageRank
Bruno Defraene1143.37
Toon van Waterschoot215714.29
Moritz Diehl31343134.37
Marc Moonen43673326.91