Assessing Deep Generative Models on Time Series Network Data

Assessing Deep Generative Models on Time Series Network Data

To achieve zero touch automation in next generation wireless networks through artificial intelligence (AI), large amounts of training data is required. This training data is publicly unavailable and is a major hindrance in research on AI applications to wireless communication. One solution is using...

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Bibliographic Details
Main Authors: Muhammad Haris Naveed, Umair Sajid Hashmi, Nayab Tajved, Neha Sultan, Ali Imran
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Machine learning
GAN
TimeGAN
PAR
DoppleGANger
time series
Online Access:https://ieeexplore.ieee.org/document/9781420/

Internet

https://ieeexplore.ieee.org/document/9781420/

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