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Frequency estimation of a single real-valued sinusoid: An invariant function approach
Date
2021-08-01
Author
Candan, Çağatay
Çelebi, Utku
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An invariant function approach for the computationally efficient (non-iterative and gridless) maximum likelihood (ML) estimation of unknown parameters is applied on the real-valued sinusoid frequency estimation problem. The main attraction point of the approach is its potential to yield a ML-like performance at a significantly reduced computational load with respect to conventional ML estimator that requires repeated evaluation of an objective function or numerical search routines. The numerical results indicate that the suggested estimator closely tracks the Cramer-Rao bound in the asymptotic region and performs very close to the ML estimator in other regions.
URI
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85104126929&origin=inward
https://hdl.handle.net/11511/90139
Journal
Signal Processing
DOI
https://doi.org/10.1016/j.sigpro.2021.108098
Collections
Department of Electrical and Electronics Engineering, Article
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Ç. Candan and U. Çelebi, “Frequency estimation of a single real-valued sinusoid: An invariant function approach,”
Signal Processing
, pp. 0–0, 2021, Accessed: 00, 2021. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85104126929&origin=inward.