Synthetic Signal Generation Using Time Series Clustering and Conditional Generative Adversarial Network
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-31956-3_21
Reference24 articles.
1. Priemer, R.: Introductory signal processing. In: Advanced Series in Electrical and Computer Engineering. World Scientific Publishing Company (1990). https://books.google.com.tr/books?id=5AM8DQAAQBAJ
2. Liu, W., Wang, Z., Liu, X., Zeng, N., Liu, Y., Alsaadi, F.E.: A survey of deep neural network architectures and their applications. Neurocomputing 234, 11–26 (2017). https://doi.org/10.1016/j.neucom.2016.12.038
3. Springer Optimization and Its Applications;SI Nikolenko,2021
4. Esteban, C., Hyland, S.L., Rätsch, G.: Real-valued (medical) time series generation with recurrent conditional GANs (2017). https://doi.org/10.48550/ARXIV.1706.02633
5. Smith, K.E., Smith, A.O.: Conditional GAN for timeseries generation (2020). https://doi.org/10.48550/ARXIV.2006.16477
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