A feedforward WaveNet trained on measured parametric loudspeaker data compensates nonlinear distortion better than Volterra inverse filters, lowering average THD to 4.55% and IMD to 2.47%.
A study for the realization of a parametric loudspeaker,
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Deep Learning-Based Approach for Identification and Compensation of Nonlinear Distortions in Parametric Array Loudspeakers
A feedforward WaveNet trained on measured parametric loudspeaker data compensates nonlinear distortion better than Volterra inverse filters, lowering average THD to 4.55% and IMD to 2.47%.