Blind Adaptive SIMO Acoustic System Identification Using a Locally Optimal Step-Size

Hu M, Sharma D, Doclo S, Brookes M, Naylor PA. Blind Adaptive SIMO Acoustic System Identification Using a Locally Optimal Step-Size. In: AES Conference: 60th International Conference: Dereverberation and Reverberation of Audio, Music, and Speech. Audio Engineering Society; 2016. Paper 6-2. Available from: https://aes.org/publications/elibrary-page/?id=18082

@inproceedings{Hu2016_18082,
  author = {Hu, Mathieu and Sharma, Dushyant and Doclo, Simon and Brookes, Mike and Naylor, Patrick A.},
  title = {{Blind Adaptive SIMO Acoustic System Identification Using a Locally Optimal Step-Size}},
  booktitle = {AES Conference: 60th International Conference: Dereverberation and Reverberation of Audio, Music, and Speech},
  note = {Paper 6-2},
  year = {2016},
  month = jan,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=18082}
}

TY  - CPAPER
TI  - Blind Adaptive SIMO Acoustic System Identification Using a Locally Optimal Step-Size
AU  - Hu, Mathieu
AU  - Sharma, Dushyant
AU  - Doclo, Simon
AU  - Brookes, Mike
AU  - Naylor, Patrick A.
T2  - AES Conference: 60th International Conference: Dereverberation and Reverberation of Audio, Music, and Speech
M1  - Paper 6-2
PY  - 2016
DA  - 2016/01/06
UR  - https://aes.org/publications/elibrary-page/?id=18082
PB  - Audio Engineering Society
LA  - en
AB  - Blind adaptive identification of a Single-Input Multiple-Output (SIMO) acoustic system has useful applications including acoustic environment sensing, source localization and, in combination with multichannel equalization, dereverberation. An empirically chosen step-size is usually employed in blind system identification algorithms based on cross-relation error minimization. Although some adaptive step-size approaches have been proposed in the literature, the derivations rely, in some cases, on coarse approximations. In this paper, a locally optimal adaptive-step size exploiting the algebraic nature of the problem is derived. Experimental results using simulated room impulse responses show that the proposed algorithm has higher initial convergence rate.
ER  -