Signal Recovery from Randomly Quantized Data Using Neural Network Approach

Signal Recovery from Randomly Quantized Data Using Neural Network Approach

We present an efficient scheme based on a long short-term memory (LSTM) autoencoder for accurate seismic deconvolution in a multichannel setup. The technique is beneficial for compressing massive amounts of seismic data. The proposed robust estimation ensures the recovery of sparse reflectivity from...

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Bibliographic Details
Main Author:	Ali Al-Shaikhi
Format:	Article
Language:	English
Published:	MDPI AG 2022-11-01
Series:	Sensors
Subjects:	quantization deconvolution LSTM neural network
Online Access:	https://www.mdpi.com/1424-8220/22/22/8712

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