We consider distributed linearly constrained minimum variance (LCMV) beamforming in a wireless sensor network. Each node computes an LCMV beamformer with node-specific constraint...
We consider camera self-calibration, i.e. the estimation of parameters for camera sensors, in the setting of a visual sensor network where the sensors are distributed and energy-c...
Distributed averaging describes a class of network algorithms for the decentralized computation of aggregate statistics. Initially, each node has a scalar data value, and the goal...
Abstract-- We introduce a distributed estimation algorithm for use by a collection of stochastically interacting agents. Each agent has both a discrete value and an estimate of the...
We consider distributed estimation of a time-dependent, random state vector based on a generally nonlinear/non-Gaussian state-space model. The current state is sensed by a serial ...