43 citations · 162 across the 29 of their papers we have counts for
7 papers · 1 filter
Understanding the Basis of Graph Convolutional Neural Networks via an Intuitive Matched Filtering Approach
Ljubisa Stankovic, Danilo Mandic
Graph Convolutional Neural Networks (GCNN) are becoming a preferred model for data processing on irregular domains, yet their analysis and principles of operation are rarely examin…
Convolutional Neural Networks Demystified: A Matched Filtering Perspective Based Tutorial
Ljubisa Stankovic, Danilo Mandic
Deep Neural Networks (DNN) and especially Convolutional Neural Networks (CNN) are a de-facto standard for the analysis of large volumes of signals and images. Yet, their developmen…
Dynamic Portfolio Cuts: A Spectral Approach to Graph-Theoretic Diversification
Alvaro Arroyo, Bruno Scalzo, Ljubisa Stankovic +1
Stock market returns are typically analyzed using standard regression, yet they reside on irregular domains which is a natural scenario for graph signal processing. To this end, we…
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…
On the Sparsity Bound for the Existence of a Unique Solution in Compressive Sensing by the Gershgorin Theorem
Ljubisa Stankovic
Since compressive sensing deals with a signal reconstruction using a reduced set of measurements, the existence of a unique solution is of crucial importance. The most important ap…
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…
Nonstationary Portfolios: Diversification in the Spectral Domain
Bruno Scalzo, Alvaro Arroyo, Ljubisa Stankovic +1
Classical portfolio optimization methods typically determine an optimal capital allocation through the implicit, yet critical, assumption of statistical time-invariance. Such model…