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This paper focuses on the problem of distributed composite
hypothesis testing in a network of sparsely interconnected
agents, in which only a small section of the field modeling
parametric alternatives is observable at each agent. A recursive
generalized likelihood ratio test (GLRT) type algorithm
in a distributed setup of the consensus-plus-innovations form
is proposed, in which the agents update their parameter estimates
and decision statistics by simultaneously processing
the latest sensed information (innovations) and information

ICASSP 2016 presentation, Session: SPTM-P14 - Compressed Sampling and Sparsity, Friday, March 25, 8:30-10:30

Time delay estimation refers to finding the time-differences-of-arrival between signals received at an array of sensors. In this presentation, representative applications of time delay estimation are first described. Algorithms for accurately estimating the time difference between two sensor outputs using random and deterministic signals are then presented and analyzed.

Recently, OFDM has been considered for VLC to boost data rates and combat inter-symbol interference. However, VLC-OFDM inherits the disadvantage of high PAPR from traditional RF systems. Unlike RF signaling, both the maximum and minimum of VLC signals must be considered. Additionally, in order to support dimming control, the positive and negative dynamic-range constraints could be asymmetric. Clipping is the simplest way to satisfy the dynamic-range constraints, but it does not allow for any EVM distortion control.

This paper presents methods to compare high order networks using persistent homology. High order networks induce well-founded homolog- ical features and the difference between networks is measured by the difference between the homological features. This is a reasonable approximation to a valid metric in the space of high order networks modulo permutation isomorphisms. The approximations succeed in discriminating engineering research communities from mathematics communities.

Greedy pursuit is one of the standard approaches for sparse approximation. Since the derivation of the conventional greedy pursuit schemes, including matching pursuit (MP) and orthogonal MP (OMP), is based on the inner product space, they may not work properly in the presence of impulsive noise. In this work, we devise a new definition of correlation in lp-space with p>0, called lp-correlation, and introduce the concept of orthogonality in lp-space.