2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2015
DOI: 10.1109/icassp.2015.7177976
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Non-linear distortion reduction for a loudspeaker based on recursive source equalization

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Cited by 2 publications
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“…For such a system, the convergence of the iteration (11) with α = 1 is specifically analyzed in [24]. According to experiences from observations in [24] as well as in [27]- [29], when setting convergence rate α = 1, the iteration (11) will converge rapidly (usually 2 to 7 iterations). Therefore, to ensure the iteration converges to the predistorted signals, the number of iterations, represented by a symbol I, is set to cover the commonly-used empirical values (e.g., I = 10).…”
Section: ) Iterative Algorithm To Obtain Predistorted Signalsmentioning
confidence: 99%
“…For such a system, the convergence of the iteration (11) with α = 1 is specifically analyzed in [24]. According to experiences from observations in [24] as well as in [27]- [29], when setting convergence rate α = 1, the iteration (11) will converge rapidly (usually 2 to 7 iterations). Therefore, to ensure the iteration converges to the predistorted signals, the number of iterations, represented by a symbol I, is set to cover the commonly-used empirical values (e.g., I = 10).…”
Section: ) Iterative Algorithm To Obtain Predistorted Signalsmentioning
confidence: 99%
“…Building models of loudspeakers that are simultaneously accurate and efficient is a challenging task. Such models are useful both for transducer design purposes, and for the development of loudspeaker equalization, linearization or virtualization algorithms based on digital signal processing [3,4,5,6,7,8,9,10,11,12,13]. Particularly with the latter class of algorithms, the simulation processing is expected to be so efficient as to be suitable for on-the-fly operation.…”
Section: Introductionmentioning
confidence: 99%