Time-series Generative Adversarial Networks for Telecommunications Data Augmentation

Time-series Generative Adversarial Networks for Telecommunications Data Augmentation

Time- series Generative Adversarial Networks (TimeGAN) is proposed to overcome the GAN model’s insufficiency in producing synthetic samples that inherit the predictive ability of the original timeseries data. TimeGAN combines the unsupervised adversarial loss in the GAN framework with a supervised l...

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Bibliographic Details
Main Author: Dimyati, Hamid
Format: Others
Language:English
Published: KTH, Skolan för elektroteknik och datavetenskap (EECS) 2021
Subjects:
Telecommunication
Time- series Forecasting
Data Augmentation
Generative Adversarial Networks
Telekommunikation
Prognoser för Tidsserier
Dataförstoring
Computer and Information Sciences
Data- och informationsvetenskap
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-303494

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http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-303494

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