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October 10, 2025Open Access

A Noise Resilient Approach for Robust Hurst Exponent Estimation

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Authors

MPMalith PremarathnaFRFabrizio RuggeriDVDixon Vimalajeewa

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Overview

Novel noise-controlled alpheee improves hurst exponent accuracy, addressing noise challenges in wavelet analysis.

Key Points

  • NC-ALPHEE significantly enhances hurst exponent estimation in noisy environments, improving reliability.
  • Under noise conditions, NC-ALPHEE consistently outperforms traditional averaging methods used in hurst exponent estimation.
  • Simulations reveal that NC-ALPHEE matches ALPHEE's accuracy in noise-free data while maintaining performance in noise.
  • The proposed method incorporates neural networks to adaptively combine multiple level-pairwise estimates, enhancing results.

Cite This Study

Premarathna et al. (2025) studied this question.

synapsesocial.com/papers/68e997abe14057276da7f245https://doi.org/10.48550/arxiv.2510.04811
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