A Hybrid Deep Physics Neural Network Model for Unsupervised Autoencoder to Perform Data Conditioning

Denoising, smoothing, missing data, and outlier issues that occur in many fields involve finding models for noise and data. However, the models often make assumptions of the noise, such as white noise, Gaussian noise, etc. Numerical methods [wavelets, Fourier transforms, Kalman filter, principal com...

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Bibliographic Details

Published in:	IEEE International Symposium on Signal Processing and Information Technology pp. 1 - 7
Main Authors:	Madasu, Srinath, Rangarajan, Keshava P.
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.12.2019
Subjects:	autoencoder data conditioning data denoising data-driven deep neural network hybrid model
ISSN:	2641-5542
Online Access:	Get full text
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