Results 1 to 10 of about 636 (117)

Grid-Graph Signal Processing (Grid-GSP): A Graph Signal Processing Framework for the Power Grid [PDF]

IEEE Transactions on Signal Processing, 2021
The underlying theme of this paper is to explore the various facets of power systems data through the lens of graph signal processing (GSP), laying down the foundations of the Grid-GSP framework. Grid-GSP provides an interpretation for the spatio-temporal properties of voltage phasor measurements, by showing how the well-known power systems modeling ...
Raksha Ramakrishna, Anna Scaglione
exaly   +3 more sources

Graph Signal Processing: Dualizing GSP Sampling in the Vertex and Spectral Domains

IEEE Transactions on Signal Processing, 2022
V2: Added missing space in arXiv title, V3: Revised paper following journal ...
John Shi, JOSÉ M F Moura
exaly   +3 more sources

GSP Cochlea: A graph signal processing approach for studying sound encoding. [PDF]

PNAS Nexus
Abstract Humans are able to hear in a variety of complicated acoustic environments. This feat begins in the peripheral auditory system, where the cochlea collects and transmits thousands of individual bits of sound data to the brain. Here, we introduce GSP Cochlea: a graph signal processing-based framework to investigate and visualize
Bonomo ME, Segarra S, Raphael RM.
europepmc   +2 more sources

A joint range–angle–velocity estimation algorithm for FDA-MIMO radar based on graph signal processing [PDF]

Scientific Reports
In this paper, a novel Frequency Diverse Array–Multiple Input Multiple Output (FDA-MIMO) radar parameter estimation algorithm based on Graph Signal Processing (GSP) is proposed for joint range–angle–velocity estimation.
Qinlin Li, Ao Meng, Kefei Liao, Ningbo Xie, Xianglai Liao, Hanbo Chen, Kamarul Hawari Bin Ghazali   +6 more
doaj   +2 more sources

Topological Signal Processing from Stereo Visual SLAM [PDF]

Sensors
Topological signal processing is emerging alongside Graph Signal Processing (GSP) in various applications, incorporating higher-order connectivity structures—such as faces—in addition to nodes and edges, for enriched connectivity modeling.
Eleonora Di Salvo, Tommaso Latino, Maria Sanzone, Alessia Trozzo, Stefania Colonnese   +4 more
doaj   +2 more sources

State Estimation in Partially Observable Power Systems via Graph Signal Processing Tools

Sensors, 2023
This paper considers the problem of estimating the states in an unobservable power system, where the number of measurements is not sufficiently large for conventional state estimation.
Lital Dabush, Ariel Kroizer, Tirza Routtenberg   +2 more
doaj   +3 more sources

ERG-Graph: Graph Signal Processing of the Electroretinogram for Classification of Neurodevelopmental Disorders [PDF]

Bioengineering
Objective biomarkers for neurodevelopmental disorders remain an unmet clinical need. The electroretinogram (ERG), a non-invasive recording of the retinal response to light, has shown promise as a physiological marker for autism spectrum disorder (ASD ...
Luis Roberto Mercado-Diaz, Javier O. Pinzon-Arenas, Paul A. Constable, Irene O. Lee, Lynne Loh, Dorothy A. Thompson, Hugo F. Posada-Quintero   +6 more
doaj   +2 more sources

RETRACTED ARTICLE: Spectral feature modeling with graph signal processing for brain connectivity in autism spectrum disorder

Scientific Reports
Autism spectrum disorder (ASD) is a complex neurodevelopmental condition associated with disrupted brain connectivity. Traditional graph-theoretical approaches have been widely employed to study ASD biomarkers; however, these methods are often limited to
Ayesha Jabbar, Huang Jianjun, Muhammad Kashif Jabbar, Khalil ur Rehman, Anas Bilal   +4 more
doaj   +2 more sources

A Dimensionality Reduction Approach for Motor Imagery Brain–Computer Interface Using Functional Clustering and Graph Signal Processing [PDF]

Journal of Medical Signals and Sensors
Background: This paper introduces an approach for dimensionality reduction and classification of electroencephalogram signals in motor imagery brain–computer interface (MI-BCI) systems.
Mohammad Davood Khalili, Vahid Abootalebi, Hamid Saeedi-Sourck   +2 more
doaj   +2 more sources

Graphs Constructed from Instantaneous Amplitude and Phase of Electroencephalogram Successfully Differentiate Motor Imagery Tasks [PDF]

Journal of Medical Signals and Sensors
Background: Accurate classification of electroencephalogram (EEG) signals is challenging given the nonlinear and nonstationary nature of the data as well as subject-dependent variations.
Maliheh Miri, Vahid Abootalebi, Hamid Saeedi-Sourck, Dimitri Van De Ville, Hamid Behjat   +4 more
doaj   +2 more sources