Training and test dataset for CNN-LSTM model for GW waveform extraction

Chayan Chatterjee (Contributor)

School of Physics, Mathematics and Computing

Dataset

Description

This repository contains training and test samples corresponding to the paper, 'Extraction of binary black hole gravitational wave signals from detector data using deep learning', Chatterjee et al., Phys. Rev. D 104, 064046 (2021).

Date made available	16 Sept 2021
Publisher	Zenodo

DOI
10.5281/zenodo.7751012

1 Article

Extraction of binary black hole gravitational wave signals from detector data using deep learning
Chatterjee, C., Wen, L., Diakogiannis, F. & Vinsen, K., 15 Sept 2021, In: Physical Review D. 104, 6, 064046.
Research output: Contribution to journal › Article › peer-review

Open Access
38 Citations (Web of Science)

Training and test dataset for CNN-LSTM model for GW waveform extraction
Chatterjee, C. (Creator), Zenodo, 2021
DOI: 10.5281/zenodo.7751013, https://zenodo.org/record/7751013
Dataset

Training and test dataset for CNN-LSTM model for GW waveform extraction

Description

DOI

Research output

Extraction of binary black hole gravitational wave signals from detector data using deep learning

Datasets

Training and test dataset for CNN-LSTM model for GW waveform extraction

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