In stochastic thresholding, the threshold for quantization of a signal is randomized. An estimator based on quantized signal data can be optimized through stochastic thresholding. ...
We investigate power estimation on a random noise from measurements taken by one-bit quantizers, with an efficacy assessed by the Fisher information. In isolated quantizers, an op...
The problem of distributed Bayesian estimation is considered in the context of a wireless sensor network. The Bayesian estimation performance is analyzed in terms of the expected F...
In this paper, we propose a particle filtering approach for the problem of registering two point sets that differ by a rigid body transformation. Typically, registration algorithms...
Romeil Sandhu, Samuel Dambreville, Allen Tannenbau...
—The implementation of distributed network utility maximization (NUM) algorithms hinges heavily on information feedback through message passing among network elements. In practic...