Theoretical results have been validated through computer simulations.
📌 3 Key Takeaways
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Objective & Hypothesis:An exact closed-form expression for the variance of frequency estimators proposed by Jacobsen and Kootsookos (2007) and Candan (2011) has been derived.
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Key Findings & Data:Additionally, an approximate variance formula applicable for sufficiently large data lengths is provided.
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Conclusion & Impact:Theoretical results have been validated through computer simulations.
🔬Design:Araştırma Makalesi
📍Scope:2007 Verileri
⚙️Variables:Frekans kestirimi · Kompleks sinüzoid · Değişinti analizi
Abstract
An exact closed-form expression for the variance of frequency estimators proposed by Jacobsen and Kootsookos (2007) and Candan (2011) has been derived. Additionally, an approximate variance formula applicable for sufficiently large data lengths is provided. Theoretical results have been validated through computer simulations.
Özet
Jacobsen ve Kootsookos (2007) ve Candan (2011) makalelerinde önerilen frekans kestiricilerinin değişintisi için bir kesin kapalı biçim ifadesi türetilmiştir. Ek olarak, yeterince büyük veri uzunlukları için geçerli olan yaklaşık bir değişinti formülü verilmiştir. Teorik sonuçlar bilgisayar simülasyonları ile doğrulanmıştır.
Keyta, B. M., Dilaveroğlu, E. (2025). AN EXACT ANALYSIS OF FINE RESOLUTION FREQUENCY ESTIMATION METHOD FROM THREE DFT SAMPLES. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi, Cilt: 30 Sayı: 1, 221–230. https://doi.org/10.17482/uumfd.1583908
Candan, Ç. (2011) A method for fine resolution frequency estimation from three DFT samples, IEEE Signal Processing Letters, 18(6), 351-354. doi: 10.1109/LSP.2011.2136378
Candan, Ç. (2013) Analysis and further improvement of fine resolution frequency estimation method from three DFT samples, IEEE Signal Processing Letters, 20(9), 913-916. doi: 10.1109/LSP.2013.2273616
Jacobsen, E. and Kootsookos, P. (2007) Fast, accurate frequency estimators, IEEE Signal Processing Magazine, 24(3), 123-125.
Kay, S.M. (1993) Fundamentals of Statistical Signal Processing: Estimation Theory, Prentice-Hall, New Jersey.
Papoulis, A. (1991) Probability, Random Variables, and Stochastic Processes, McGraw-Hill, New York.