In this article, we describe a general algorithmic framework for solving linear signal or
feature fusion optimization problems in a distributed setting, for example in a wireless sensor …

A wireless sensor network often relies on a fusion center to process the data collected by
each of its sensing nodes. Such an approach relies on the continuous transmission of raw …

In this article, the problems of decentralized Singular Value Decomposition (d-SVD) and
decentralized Principal Component Analysis (d-PCA) are studied, which are fundamental in …

Computing the optimal solution to a spatial filtering problems in a Wireless Sensor Network
can incur large bandwidth and computational requirements if an approach relying on data …

The Distributed Adaptive Signal Fusion (DASF) framework is a meta-algorithm for computing
data-driven spatial filters in a distributed sensing platform with limited bandwidth and …

Spatial filtering procedures aim to optimally fuse the different signals collected in a sensor
array, by exploiting their inter-channel correlations. If the sensors are physically distributed …

The distributed adaptive signal fusion (DASF) framework allows to solve spatial filtering
optimization problems in a distributed and adaptive fashion over a bandwidth-constrained …

With the emergence of wireless sensor networks (WSNs), many traditional signal processing
tasks are required to be computed in a distributed fashion, without transmissions of the raw …

The distributed adaptive signal fusion (DASF) framework has been proposed as a generic
method to solve spatial filtering and signal fusion problems in a distributed fashion over a …