Zobrazeno 1 - 10 of 21 pro vyhledávání: '"Sreeraj Rajendran"'
1
Combined RF-Based Drone Detection and Classification
Autor: Sofie Pollin, Sreeraj Rajendran, Sanjoy Basak, Bart Scheers
Publikováno v: IEEE Transactions on Cognitive Communications and Networking. 8:111-120
Despite several beneficial applications, unfortunately, drones are also being used for illicit activities such as drug trafficking, firearm smuggling or to impose threats to security-sensitive places like airports and nuclear power plants. The existi
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::85ee57c606bd69b464e15ac479e61b64
https://doi.org/10.1109/tccn.2021.3099114
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4
Learning the unknown: Improving modulation classification performance in unseen scenarios
Autor: Erma Perenda∗, Sreeraj Rajendran∗
Learning the unknown: Improving modulation classification performance in unseen scenarios Erma Perenda∗, Sreeraj Rajendran∗, Gerome Bovet†, Sofie Pollin∗and Mariya Zheleva‡{erma.perenda, sreeraj.rajendran, sofie.pollin}@esat.kuleuven.be, ge
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2f70bfdac497c5beb84c085fa5b6ebc8
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7
2D Angularly Dependent Array Error Calibration for 1D Array via Neural Network with Local Manifold Interpolation
Autor: Sofie Pollin, Sreeraj Rajendran, Y. Pan
Publikováno v: Radioengineering. 2021 vol. 30, č. 3, s. 547-555. ISSN 1210-2512
Radioengineering, Vol 30, Iss 3, Pp 547-555 (2021)
The calibration of the angularly dependent array error is a challenging task for signal processing. In this paper, we propose a neural network (NN)-based two-dimensional (2D) calibration method for a linear array. Firstly, the array steering vectors
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7185c48f5f87088acf941c0c940b067a
https://hdl.handle.net/11012/201827
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8
Unsupervised Wireless Spectrum Anomaly Detection With Interpretable Features
Autor: Sofie Pollin, Vincent Lenders, Wannes Meert, Sreeraj Rajendran
Publikováno v: IEEE Transactions on Cognitive Communications and Networking. 5:637-647
Detecting anomalous behavior in wireless spectrum is a demanding task due to the sheer complexity of the electromagnetic spectrum use. Wireless spectrum anomalies can take a wide range of forms from the presence of an unwanted signal in a licensed ba
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::52d6d7f2d4e76e133a4f2c9cb84eb5a5
https://doi.org/10.1109/tccn.2019.2911524
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9
Learning the unknown: Improving modulation classification performance in unseen scenarios
Autor: Gérôme Bovet, Mariya Zheleva, Sofie Pollin, Sreeraj Rajendran, Erma Perenda
Publikováno v: INFOCOM
Automatic Modulation Classification (AMC) is significant for the practical support of a plethora of emerging spectrum applications, such as Dynamic Spectrum Access (DSA) in 5G and beyond, resource allocation, jammer identification, intruder detection
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::21cbfde17db0c644cb469fd8651101c9
https://doi.org/10.1109/infocom42981.2021.9488835
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10
Evolutionary Optimization of Residual Neural Network Architectures for Modulation Classification
Autor: Sofie Pollin, Sreeraj Rajendran, Mariya Zheleva, Gérôme Bovet, Erma Perenda
Automatic Modulation Classification (AMC) receives significant interest in the context of current and future wireless communication systems. Deep learning emerged as a powerful AMC tool, as it allows for the joint learning of discriminative features,
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::34007fc123b0c02b5178fd782ac14072
https://doi.org/10.36227/techrxiv.14528778
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