The objective of this paper is to review the theories and approaches of multisensor fusion
and integration (MFI) with its application in mechatronics. MFI helps the system perceiving …

We consider the problem of distributed estimation, where a set of nodes is required to
collectively estimate some parameter of interest from noisy measurements. The problem is …

We study the problem of distributed Kalman filtering and smoothing, where a set of nodes is
required to estimate the state of a linear dynamic system from in a collaborative manner. Our …

We formulate and study distributed estimation algorithms based on diffusion protocols to
implement cooperation among individual adaptive nodes. The individual nodes are …

We study the problem of distributed estimation over adaptive networks where a collection of
nodes are required to estimate in a collaborative manner some parameter of interest from …

As is well known, Hessian-based adaptive filters (such as the recursive-least squares
algorithm (RLS) for supervised adaptive filtering, or the Shalvi-Weinstein algorithm (SWA) for …

The least mean square (LMS) based linear adaptive algorithms are commonly used for
acoustic feedback cancellation (AFC) in digital hearing aids, given the simplicity, tracking …

We present diffusion algorithms for distributed estimation and detection over networks that
endow all nodes with both spatial cooperation abilities and temporal processing abilities …

Nonstationary environments are ubiquitous in communications and acoustic systems. The
ability to track their dynamics is one of the most desirable features of adaptive processing …

We propose a robust and low complexity scheme to estimate and track carrier frequency
from signals traveling under low signal-to-noise ratio (SNR) conditions in highly …