Orthogonal Features-based EEG Signal Denoising using Fractionally Compressed AutoEncoder

A fractional-based compressed auto-encoder architecture has been introduced to solve the problem of denoising electroencephalogram (EEG) signals. The architecture makes use of fractional calculus to calculate the gradients during the backpropagation process, as a result of which a new hyper-paramete...

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Bibliographic Details

Published in:	arXiv.org
Main Authors:	Nagar, Subham, Kumar, Ahlad, Swamy, M N S
Format:	Paper
Language:	English
Published:	Ithaca Cornell University Library, arXiv.org 16.02.2021
Subjects:	Algorithms Back propagation Back propagation networks Coders Compression ratio Compression tests Computer architecture Electroencephalography Electronic devices Fractional calculus Neural networks Noise reduction Singular value decomposition
ISSN:	2331-8422
Online Access:	Get full text
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