Interpolation of loudspeaker level balloons from polar measurements by using deep learning

Catala Iborra VM. Interpolation of loudspeaker level balloons from polar measurements by using deep learning. In: Express Paper. Audio Engineering Society; 2024. Paper 202. Available from: https://aes.org/publications/elibrary-page/?id=22548

@inproceedings{CatalaIborra2024_22548,
  author = {Catala Iborra, Victor Manuel},
  title = {{Interpolation of loudspeaker level balloons from polar measurements by using deep learning}},
  note = {Paper 202},
  year = {2024},
  month = jun,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=22548}
}

TY  - CPAPER
TI  - Interpolation of loudspeaker level balloons from polar measurements by using deep learning
AU  - Catala Iborra, Victor Manuel
M1  - Paper 202
PY  - 2024
DA  - 2024/06/06
UR  - https://aes.org/publications/elibrary-page/?id=22548
PB  - Audio Engineering Society
LA  - en
AB  - Complete radiation balloons are needed to analyze the performance of loudspeakers and to perform accurate tunning and electroacoustic predictions of loudspeaker systems. A method is proposed to obtain full radiation balloons from horizontal and vertical polar measurements by using U-Net, a deep learning architecture widely applied for image processing. Mean absolute errors lower than 4 dB were obtained on test data.
ER  -