Application of AI techniques for Nonlinear control of loudspeakers

Brunet PM, Li Y, Kubota GS, Mariajohn A. Application of AI techniques for Nonlinear control of loudspeakers. In: AES Convention 151. Audio Engineering Society; 2021. Paper 10535. Available from: https://aes.org/publications/elibrary-page/?id=21499

@inproceedings{Brunet2021_21499,
  author = {Brunet, Pascal M. and Li, Yuan and Kubota, Glenn S. and Mariajohn, Aaquila},
  title = {{Application of AI techniques for Nonlinear control of loudspeakers}},
  booktitle = {AES Convention 151},
  note = {Paper 10535},
  year = {2021},
  month = oct,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=21499}
}

TY  - CPAPER
TI  - Application of AI techniques for Nonlinear control of loudspeakers
AU  - Brunet, Pascal M.
AU  - Li, Yuan
AU  - Kubota, Glenn S.
AU  - Mariajohn, Aaquila
T2  - AES Convention 151
M1  - Paper 10535
PY  - 2021
DA  - 2021/10/06
UR  - https://aes.org/publications/elibrary-page/?id=21499
PB  - Audio Engineering Society
LA  - en
AB  - To obtain high loudness, with good bass extension, while keeping distortion low, and ensuring mechanical protection, the motion of the loudspeaker diaphragm needs to be controlled accurately. Actual solutions for nonlinear control of loudspeakers are complex and difficult to implement and tune. They are limited in accuracy due to physical models that do not completely capture the complexity of the loudspeaker. Furthermore, physical model parameters are difficult to estimate. We present here a novel approach that uses a Neural Network to directly map the diaphragm displacement to the input voltage, allowing us to “invert” the loudspeaker. This technique allows control and linearization of the loudspeaker without theoretical assumptions. It is also simpler to implement.
ER  -