Abdolee, Reza
Champagne, Benoit
Sayed, Ali H.
Diffusion LMS for source and process estimation in sensor networks
IEEE Statistical Signal Processing Workshop (SSP)
IEEE Statistical Signal Processing Workshop (SSP)
IEEE Statistical Signal Processing Workshop (SSP)
IEEE Statistical Signal Processing Workshop (SSP)
2012
2012
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.
IEEE
IEEE Statistical Signal Processing Workshop (SSP)
Conference Papers
10.1109/SSP.2012.6319649