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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
The results of a simulation prove the performances of the new denoising method.
📌 3 Key Takeaways
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Objective & Hypothesis:In 1992 David Donoho introduced the term denoising in connection with the adaptive nonlinear filtering in the wavelets transform domain.
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Key Findings & Data:Despite its advantages this method has not be used yet in the communications field.
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Conclusion & Impact:The results of a simulation prove the performances of the new denoising method.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters
Abstract
In 1992 David Donoho introduced the term denoising in connection with the adaptive nonlinear filtering in the wavelets transform domain. Despite its advantages this method has not be used yet in the communications field. The goal of this paper is to improve this method and to apply it in communications. The improvements are a new threshold's value searching method and the use of a new discrete wavelet transform. This new transform enhances the diversity in the wavelets transform domain. The results of a simulation prove the performances of the new denoising method.
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Cite This Article
ISAR, A., ISAR, D. (2022). Adaptive denoising of low SNR signals. ARI The Bulletin of the Istanbul Technical University, Cilt: 53 - Sayı: 2, 31–37. https://ajindex.com/articles/448162