activity
20172026
most citedGraph Signal Processing -- Part II: Processing and Analyzing Signals on Graphs

11 citations · 42 across the 11 of their papers we have counts for

collaborators

14 papers

cs.LG2026

GraphNNK -- Graph Classification and Interpretability

Zeljko Bolevic, Milos Brajovic, Isidora Stankovic +1

Graph Neural Networks (GNNs) have become a standard approach for learning from graph-structured data. However, their reliance on parametric classifiers (most often linear softmax l…

cs.IT2023

Fourier Analysis of Signals on Directed Acyclic Graphs (DAG) Using Graph Zero-Padding

Ljubisa Stankovic, Milos Dakovic, Ali Bagheri Bardi +2

Directed acyclic graphs (DAGs) are used for modeling causal relationships, dependencies, and flows in various systems. However, spectral analysis becomes impractical in this settin…

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★ 7 cited

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.IT2020★ 6 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.IT2019★ 11 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…

cs.IT2019★ 10 cited

Graph Signal Processing -- Part I: Graphs, Graph Spectra, and Spectral Clustering

Ljubisa Stankovic, Danilo Mandic, Milos Dakovic +3

The area of Data Analytics on graphs promises a paradigm shift as we approach information processing of classes of data, which are typically acquired on irregular but structured do…

eess.SP2019★ 2 cited

Vertex-Frequency Graph Signal Processing: A review

Ljubisa Stankovic, Danilo P. Mandic, Milos Dakovic +4

Graph signal processing deals with signals which are observed on an irregular graph domain. While many approaches have been developed in classical graph theory to cluster vertices…

cs.IT2019

Quantization in Compressive Sensing: A Signal Processing Approach

Isidora Stankovic, Milos Brajovic, Milos Dakovic +2

Influence of the finite-length registers and quantization effects on the reconstruction of sparse and approximately sparse signals is analyzed in this paper. For the nonquantized m…

cs.IT2019★ 2 cited

On the Decomposition of Multivariate Nonstationary Multicomponent Signals

Ljubisa Stankovic, Milos Brajovic, Milos Dakovic +1

With their ability to handle an increased amount of information, multivariate and multichannel signals can be used to solve problems normally not solvable with signals obtained fro…

cs.CV2017

Detection of irregular QRS complexes using Hermite Transform and Support Vector Machine

Zoja Vulaj, Milos Brajovic, Andjela Draganic +1

Computer based recognition and detection of abnormalities in ECG signals is proposed. For this purpose, the Support Vector Machines (SVM) are combined with the advantages of Hermit…

cs.CE2017★ 4 cited

A tool for ECG signal analysis using standard and optimized Hermite transform

Zoja Vulaj, Andjela Draganic, Milos Brajovic +1

The development of a system that would ease the diagnosis of heart diseases would also fasten the work of the cardiologic department in hospitals and facilitate the monitoring of p…