2 papers
cs.IT2016
On Sparsity by NUV-EM, Gaussian Message Passing, and Kalman Smoothing
Hans-Andrea Loeliger, Lukas Bruderer, Hampus Malmberg +2
Normal priors with unknown variance (NUV) have long been known to promote sparsity and to blend well with parameter learning by expectation maximization (EM). In this paper, we adv…
cs.AR2014
A Signal Processor for Gaussian Message Passing
Harald Kröll, Stefan Zwicky, Reto Odermatt +3
In this paper, we present a novel signal processing unit built upon the theory of factor graphs, which is able to address a wide range of signal processing algorithms. More specifi…