doi:10.1109/SSP.2012.6319649
Abdolee, Reza
Champagne, Benoit
Sayed, Ali H.
Diffusion LMS for source and process estimation in sensor networks
We develop a least mean-squares (LMS) diffusion strategy for sensor network applications where it is desired to estimate parameters of physical phenomena that vary over space. In particular, we consider a regression model with space-varying parameters that captures the system dynamics over time and space. We use a set of basis functions such as sinusoids or B-spline functions to replace the space-variant (local) parameters with space-invariant (global) parameters, and then apply diffusion adaptation to estimate the global representation. We illustrate the performance of the algorithm via simulations.
2017-12-19T10:06:16Z
http://infoscience.epfl.ch/record/233422
http://infoscience.epfl.ch/record/233422