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1-D Convolutional Neural Networks for Signal Processing Applications
Qatar University, Qatar.
Izmir University of Economics, Turkey.
Qatar University, Qatar.ORCID-id: 0000-0003-0530-9552
Qatar University, Qatar.
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2019 (Engelska)Ingår i: 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing: May 12–17, 2019 Brighton Conference Centre Brighton, United Kingdom, IEEE, 2019, s. 8360-8364Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

1D Convolutional Neural Networks (CNNs) have recently become the state-of-the-art technique for crucial signal processing applications such as patient-specific ECG classification, structural health monitoring, anomaly detection in power electronics circuitry and motor-fault detection. This is an expected outcome as there are numerous advantages of using an adaptive and compact 1D CNN instead of a conventional (2D) deep counterparts. First of all, compact 1D CNNs can be efficiently trained with a limited dataset of 1D signals while the 2D deep CNNs, besides requiring 1D to 2D data transformation, usually need datasets with massive size, e.g., in the "Big Data" scale in order to prevent the well-known "overfitting" problem. 1D CNNs can directly be applied to the raw signal (e.g., current, voltage, vibration, etc.) without requiring any pre- or post-processing such as feature extraction, selection, dimension reduction …

Ort, förlag, år, upplaga, sidor
IEEE, 2019. s. 8360-8364
Serie
Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing., E-ISSN 1520-6149
Nationell ämneskategori
Signalbehandling
Forskningsämne
Fysik, Vågor och signaler
Identifikatorer
URN: urn:nbn:se:lnu:diva-89756DOI: 10.1109/ICASSP.2019.8682194ISBN: 9781479981311 (tryckt)ISBN: 9781479981328 (digital)OAI: oai:DiVA.org:lnu-89756DiVA, id: diva2:1362698
Konferens
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 12-17 May, 2019, Brighton
Tillgänglig från: 2019-10-21 Skapad: 2019-10-21 Senast uppdaterad: 2019-12-18Bibliografiskt granskad

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