On the Use of Concentrated Time–Frequency Representations as Input to a Deep Convolutional Neural Network: Application to Non Intrusive Load Monitoring

On the Use of Concentrated Time–Frequency Representations as Input to a Deep Convolutional Neural Network: Application to Non Intrusive Load Monitoring

Since decades past, time–frequency (TF) analysis has demonstrated its capability to efficiently handle non-stationary multi-component signals which are ubiquitous in a large number of applications. TF analysis us allows to estimate physics-related meaningful parameters (e.g., <inline-formula>&...

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Bibliographic Details
Main Authors: Sarra Houidi, Dominique Fourer, François Auger
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Entropy
Subjects:
non-intrusive load monitoring (NILM)
time–frequency representation (TFR)
deep learning
convolutional neural network (CNN)
synchrosqueezing
Layer wise relevance propagation (LRP)
Online Access:https://www.mdpi.com/1099-4300/22/9/911

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https://www.mdpi.com/1099-4300/22/9/911

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