Results 51 to 60 of about 5,220,012 (288)

Speaker verification method based on cross-domain attentive feature fusion

open access: yesTongxin xuebao, 2023
Aiming at the problem that the lack of structure information among speech signal sample in the front-end acoustic features of speaker verification system, a speaker verification method based on cross-domain attentive feature fusion was proposed.Firstly ...
Zhen YANG   +3 more
doaj   +2 more sources

Introduction to the IEEE Journal on Selected Topics in Signal Processing and IEEE Transactions on Signal and Information Processing Over Networks Joint Special Issue on Graph Signal Processing

open access: yes, 2017
The papers in this special issue are intended to address some of the main research challenges in Graph Signal Processing by presenting a collection of the latest advances in the domain.
Rabbat, Michael   +4 more
core   +1 more source

Adaptive sign algorithm for graph signal processing

open access: yesSignal Processing, 2022
Efficient and robust online processing technique of irregularly structured data is crucial in the current era of data abundance. In this paper, we propose a graph/network version of the classical adaptive Sign algorithm for online graph signal estimation under impulsive noise.
Yi Yan   +2 more
openaire   +3 more sources

Graph Neural Network Sensitivity Under Probabilistic Error Model

open access: yes, 2022
Publisher Copyright: © 2022 European Signal Processing Conference, EUSIPCO. All rights reserved.Graph convolutional networks (GCNs) can successfully learn the graph signal representation by graph convolution.
Wang, Xinjue   +2 more
core  

From mice to humans—divergent strategies for intestinal homeostasis and regeneration

open access: yesFEBS Letters, EarlyView.
Recent advances such as organoid genome editing, xenotransplantation, imaging, and whole‐genome sequencing have enabled direct studies of human intestinal stem cells (ISCs). These studies reveal species‐specific features, including slower ISC proliferation, distinct injury responses, slower somatic mutation accumulation in humans, and an inverse ...
Keiko Ishikawa   +2 more
wiley   +1 more source

GSD: An R package for graph signal decomposition

open access: yesSoftwareX
Graph signals residing on the vertices of a graph have recently gained prominence in research of various fields, including neural networks, social networks, traffic patterns, and sensors.
Hyeonglae Cho, Hee-Seok Oh, Donghoh Kim
doaj   +1 more source

Graph Signal Smoothness Based Feature Learning of Brain Functional Networks in Schizophrenia

open access: yesIEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023
In this paper we study the brain functional network of schizophrenic patients based on resting-state fMRI data. Different from the region of interest (ROI)-level brain networks that describe the connectivity between brain regions, this paper constructs a
Xiaoying Song, Li Chai
doaj   +1 more source

Design and analysis strategies for robust microbiome ageing research

open access: yesFEBS Letters, EarlyView.
The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik   +5 more
wiley   +1 more source

Graph signal processing based pilot pattern design and channel estimation for OFDM system

open access: yes物联网学报, 2022
Orthogonal frequency division multiplexing (OFDM) is one of the key technologies in the physical layer of the internet of things (IoT).Pilot design and channel estimation are key issues in OFDM systems.In view of the problem of performance loss by fixed ...
Bin HE   +3 more
doaj   +2 more sources

Joint Vertex-Time Filtering on Graphs With Random Node-Asynchronous Updates

open access: yesIEEE Access, 2021
In graph signal processing signals are defined over a graph, and filters are designed to manipulate the variation of signals over the graph. On the other hand, time domain signal processing treats signals as time series, and digital filters are designed ...
Oguzhan Teke, Palghat P. Vaidyanathan
doaj   +1 more source

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