activity
20172021
most citedGraph Signal Processing -- Part II: Processing and Analyzing Signals on Graphs

11 citations · 19 across the 4 of their papers we have counts for

collaborators

11 papers

cs.IT2021

Distance and Position Estimation in Visible Light Systems with RGB LEDs

Ilker Demirel, Sinan Gezici

In this manuscript, distance and position estimation problems are investigated for visible light positioning (VLP) systems with red-green-blue (RGB) light emitting diodes (LEDs). T…

cs.IT2021

Improved Coherence Index-Based Bound in Compressive Sensing

Ljubisa Stankovic, Milos Brajovic, Danilo Mandic +2

Within the Compressive Sensing (CS) paradigm, sparse signals can be reconstructed based on a reduced set of measurements. Reliability of the solution is determined by the uniquenes…

cs.IT2020

RANSAC-Based Signal Denoising Using Compressive Sensing

Ljubisa Stankovic, Milos Brajovic, Isidora Stankovic +2

In this paper, we present an approach to the reconstruction of signals exhibiting sparsity in a transformation domain, having some heavily disturbed samples. This sparsity-driven s…

cs.IT20206 cited

Graph Signal Processing -- Part III: Machine Learning on Graphs, from Graph Topology to Applications

Ljubisa Stankovic, Danilo Mandic, Milos Dakovic +4

Many modern data analytics applications on graphs operate on domains where graph topology is not known a priori, and hence its determination becomes part of the problem definition,…

cs.IT201911 cited

Graph Signal Processing -- Part II: Processing and Analyzing Signals on Graphs

Ljubisa Stankovic, Danilo Mandic, Milos Dakovic +3

The focus of Part I of this monograph has been on both the fundamental properties, graph topologies, and spectral representations of graphs. Part II embarks on these concepts to ad…

eess.SP2019

On reconstruction algorithms for signals sparse in Hermite and Fourier domains

Milos Brajovic

This thesis consists of original contributions in the area of digital signal processing. The reconstruction of signals sparse (highly concentrated) in various transform domains is…