Generating Synthetic Data Using 2D Multifractal Detrended Fluctuation Analysis Generative Adversarial Networks

A novel 2-dimensional Multifractal Detrended Fluctuation Analysis (2D-MFDFA) as a discriminator for Generative Adversarial Networks (GAN) is presented in this work. The proposed approach demonstrates improved generated data quality at early iterations on the MNIST dataset. This algorithm produces sy...

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Bibliografische Detailangaben

Hauptverfasser:	Charudatta Gurudas Korde, K. G. Shreeharsha, R. K. Siddharth, M. H. Vasantha, Y. B. Nithin Kumar
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	IEEE 2025-01-01
Schriftenreihe:	IEEE Access
Schlagworte:	Artificial intelligence field programmable gate array generative adversarial networks machine learning multifractal detrended fluctuation analysis (MFDFA)
Online-Zugang:	https://ieeexplore.ieee.org/document/11142759/
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