Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Azari, Bahar"'
Autor:
Soltani, Nasim, Cheng, Hai, Belgiovine, Mauro, Li, Yanyu, Li, Haoqing, Azari, Bahar, D'Oro, Salvatore, Imbiriba, Tales, Melodia, Tommaso, Closas, Pau, Wang, Yanzhi, Erdogmus, Deniz, Chowdhury, Kaushik
Orthogonal Frequency Division Multiplexing (OFDM)-based waveforms are used for communication links in many current and emerging Internet of Things (IoT) applications, including the latest WiFi standards. For such OFDM-based transceivers, many core ph
Externí odkaz:
http://arxiv.org/abs/2205.06159
Autor:
Azari, Bahar, Erdoğmuş, Deniz
Learning representations through deep generative modeling is a powerful approach for dynamical modeling to discover the most simplified and compressed underlying description of the data, to then use it for other tasks such as prediction. Most learnin
Externí odkaz:
http://arxiv.org/abs/2111.01892
We propose an epidemic analysis framework for the outbreak prediction in the livestock industry, focusing on the study of the most costly and viral infectious disease in the swine industry -- the PRRS virus. Using this framework, we can predict the P
Externí odkaz:
http://arxiv.org/abs/2110.03147
Autor:
Azari, Bahar, Erdogmus, Deniz
Despite the vast success of standard planar convolutional neural networks, they are not the most efficient choice for analyzing signals that lie on an arbitrarily curved manifold, such as a cylinder. The problem arises when one performs a planar proj
Externí odkaz:
http://arxiv.org/abs/2107.12480
We introduce deep switching auto-regressive factorization (DSARF), a deep generative model for spatio-temporal data with the capability to unravel recurring patterns in the data and perform robust short- and long-term predictions. Similar to other fa
Externí odkaz:
http://arxiv.org/abs/2009.05135
Autor:
Azari, Bahar, Cheng, Hai, Soltani, Nasim, Li, Haoqing, Li, Yanyu, Belgiovine, Mauro, Imbiriba, Tales, D’Oro, Salvatore, Melodia, Tommaso, Wang, Yanzhi, Closas, Pau, Chowdhury, Kaushik, Erdoğmuş, Deniz
Publikováno v:
In Computer Networks 9 December 2022 218
The evaluation of the performance of clustered cooperative beamforming in cellular networks generally requires the solution of complex non-convex optimization problems. In this letter, a framework based on a hypergraph formalism is proposed that enab
Externí odkaz:
http://arxiv.org/abs/1510.06222
Akademický článek
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Akademický článek
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Autor:
Azari, Bahar1, Westlin, Christiana2, Satpute, Ajay B.2, Hutchinson, J. Benjamin3, Kragel, Philip A.4, Hoemann, Katie2, Khan, Zulqarnain1, Wormwood, Jolie B.5, Quigley, Karen S.2,6, Erdogmus, Deniz1, Dy, Jennifer1, Brooks, Dana H.1 brooks@ece.neu.edu, Barrett, Lisa Feldman2,7,8 l.barrett@northeastern.edu
Publikováno v:
Scientific Reports. 11/20/2020, Vol. 10 Issue 1, p1-17. 17p.