@inproceedings {Hu1559_2016,
	year = {2016},
	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 (DREAMS)},
	number = {Session 6},
	URL = {http://www.aes.org/e-lib/browse.cfm?elib=18082},
	abstract = {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.}
}