Abstract—The paper studies the convergence properties of the estimation error processes in distributed Kalman filtering for potentially unstable linear dynamical systems. In par...
Soummya Kar, Shuguang Cui, H. Vincent Poor, Jos&ea...
A fundamental problem in signal processing is to estimate signal from noisy observations. When some prior information about the statistical models of the signal and noise is avail...
Consider a scenario where a distributed signal is sparse and is acquired by various sensors that see different versions. Thus, we have a set of sparse signals with both some commo...
In Jutten’s blind separation algorithm, symmetrical distribution and statistical independence of the signal sources are assumed. When they are not satisfied, the learning proce...
We consider distributed linearly constrained minimum variance (LCMV) beamforming in a wireless sensor network. Each node computes an LCMV beamformer with node-specific constraint...