Embedded-Optimization-Based Loudspeaker Precompensation Using a Hammerstein Loudspeaker Model

作者：Defraene Bruno^*; van Waterschoot Toon; Diehl Moritz; Moonen Marc

来源：IEEE/ACM Transactions on Audio Speech and Language Processing, 2014, 22(11): 1648-1659.

DOI：10.1109/TASLP.2014.2344862

• Embedded optimization
• gradient optimization
• hammerstein model
• loudspeaker precompensation
• sound perception

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.

• 出版日期2014-11