GPU Implementation of a Frequency-Domain Modified Filtered-X LMS Algorithm for Multichannel Local Active Noise Control

Lorente J, Ferrer M, de Diego M, Belloch JA, Gonzalez A. GPU Implementation of a Frequency-Domain Modified Filtered-X LMS Algorithm for Multichannel Local Active Noise Control. In: AES Conference: 52nd International Conference: Sound Field Control - Engineering and Perception. Audio Engineering Society; 2013. Paper P-8. Available from: https://aes.org/publications/elibrary-page/?id=16895

@inproceedings{Lorente2013_16895,
  author = {Lorente, Jorge and Ferrer, Miguel and de Diego, Maria and Belloch, Jose Antonio and Gonzalez, Alberto},
  title = {{GPU Implementation of a Frequency-Domain Modified Filtered-X LMS Algorithm for Multichannel Local Active Noise Control}},
  booktitle = {AES Conference: 52nd International Conference: Sound Field Control - Engineering and Perception},
  note = {Paper P-8},
  year = {2013},
  month = sep,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=16895}
}

TY  - CPAPER
TI  - GPU Implementation of a Frequency-Domain Modified Filtered-X LMS Algorithm for Multichannel Local Active Noise Control
AU  - Lorente, Jorge
AU  - Ferrer, Miguel
AU  - de Diego, Maria
AU  - Belloch, Jose Antonio
AU  - Gonzalez, Alberto
T2  - AES Conference: 52nd International Conference: Sound Field Control - Engineering and Perception
M1  - Paper P-8
PY  - 2013
DA  - 2013/09/06
UR  - https://aes.org/publications/elibrary-page/?id=16895
PB  - Audio Engineering Society
LA  - en
AB  - Multichannel active noise control (ANC) systems are commonly based on adaptive signal processing algo- rithms that require high computational capacity, which constraints their practical implementation. Graphics Processing Units (GPUs) are well known for their potential for highly parallel data processing. Therefore, GPUs seem to be a suitable platform for multichannel scenarios. However, e cient use of parallel computa- tion in the adaptive filtering context is not straightforward due to the feedback loops. This paper presents a GPU implementation of a multichannel feedforward local ANC system based on the modified filtered-x LMS algorithm working over a real-time prototype. Details regarding the parallelization of the algorithm are given. Experimental results are presented to validate the real-time performance of the multichannel ANC GPU implementation.
ER  -