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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
Besides, the effect of the estimation of the transient starting point on the performance of the SNR estimation is investigated
📌 3 Key Takeaways
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Objective & Hypothesis:Öz In this paper, the problem of signal-to-noise ratio (SNR) estimation of noisy transient signals is considered.
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Key Findings & Data:The performance of the SNR estimator is evaluated in terms of normalized mean square error and normalized bias.
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Conclusion & Impact:Besides, the effect of the estimation of the transient starting point on the performance of the SNR estimation is investigated
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Anahtar Kelimeler SNR estimation · transient signal detection · normalized bias
Özet
Öz In this paper, the problem of signal-to-noise ratio (SNR) estimation of noisy transient signals is considered. The SNR estimation is performed based on the average energy of the transient and noise signals. The performance of the SNR estimator is evaluated in terms of normalized mean square error and normalized bias. It is shown by simulations that the SNR estimation method exhibits good estimation performance for the SNRs encountered in many practical applications. Besides, the effect of the estimation of the transient starting point on the performance of the SNR estimation is investigated
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Cite This Article
KÖSE, M., TAŞCIOĞLU, S., TELATAR, Z. (2015). SIGNAL-TO-NOISE RATIO ESTIMATION OF NOISY TRANSIENT SIGNALS. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering, Cilt: 57 - Sayı: 1, 11–19. https://ajindex.com/articles/51190