TY - GEN
T1 - Convergence properties of normalized random incremental gradient algorithms for least-squares source localization
AU - Rabbat, Michael
AU - Nedic, Angelia
PY - 2012
Y1 - 2012
N2 - We consider the problem of localizing a single source using received signal strength measurements gathered at a number of sensors. We assume that the measurements follow the standard path loss model and are corrupted by additive white Gaussian noise. Under this model, the maximum likelihood solution to the source localization problem involves solving a non-linear least squares optimization problem. We study the convergence property of a normalized incremental gradient method for solving this problem. Remarkably, despite the fact that the problem is non-convex, the normalized incremental gradient method generates a sequence of iterates which are attracted to the global optimum under some mild conditions.
AB - We consider the problem of localizing a single source using received signal strength measurements gathered at a number of sensors. We assume that the measurements follow the standard path loss model and are corrupted by additive white Gaussian noise. Under this model, the maximum likelihood solution to the source localization problem involves solving a non-linear least squares optimization problem. We study the convergence property of a normalized incremental gradient method for solving this problem. Remarkably, despite the fact that the problem is non-convex, the normalized incremental gradient method generates a sequence of iterates which are attracted to the global optimum under some mild conditions.
UR - http://www.scopus.com/inward/record.url?scp=84876222821&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84876222821&partnerID=8YFLogxK
U2 - 10.1109/ACSSC.2012.6489259
DO - 10.1109/ACSSC.2012.6489259
M3 - Conference contribution
AN - SCOPUS:84876222821
SN - 9781467350518
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 1417
EP - 1421
BT - Conference Record of the 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012
T2 - 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012
Y2 - 4 November 2012 through 7 November 2012
ER -