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Nonparametric estimation of instantaneous frequency
IEEE Transactions on Information Theory, 1997Summary: The local polynomial approximation of time-varying phase is used in order to estimate the instantaneous frequency and its derivatives for a complex-valued harmonic signal given by discrete-time observations with a noise. The considered estimators are high-order nonparametric generalizations of the short-time Fourier transform and the Wigner ...
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Frequency Offset Estimation with Increased Nyquist Frequency
2010 IEEE 72nd Vehicular Technology Conference - Fall, 2010In wireless communication systems, there is a need to estimate and compensate for frequency offsets. What is common to frequency offset estimators, is that they only can give correct results within a certain range, up to the Nyquist frequency. This makes a difference especially in OFDM systems with pilots only at certain symbols, such as LTE.
Niklas Andgart, Fredrik Nordström
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Algorithms for estimating instantaneous frequency
Signal Processing, 2004Three algorithms to estimate instantaneous frequency of a frequency-modulated signal is discussed. These algorithms are based on Hilbert transform, Haar wavelet, and generalized pencil of function (GPOF) methods. While GPOF-based frequency detection method appears to be least sensitive to noise, wavelet-based method is easiest to implement.
Jaideva C. Goswami, Albert E. Hoefel
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An estimation method of closed frequencies
Asia-Pacific Conference on Circuits and Systems, 2003Analyzing a spectrum is a good way to estimate the frequency-components (input frequencies) of an input signal, because the spectrum is calculated by some functions that are maximum at input frequencies (A. Papoulis, Circuits and Systems: A Modern Approach, p.391, Holt, Rinehart and Winston, Inc., New York, 1980).
Rinji Abe, Noriyoshi Kambayashi
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On Frequency Offset Estimation for OFDM
IEEE Transactions on Wireless Communications, 2013This paper presents a comparative study of Schmidl-Cox (SC) and Morelli-Mengali (MM) algorithms for frequency offset estimation in OFDM, along with a new least squares (LS) and a new modified SC algorithm. All algorithms have comparable accuracy approaching asymptotically the Cramer-Rao bound.
Zoran Cvetkovic +2 more
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2012
In this section, we provide different estimation procedures of the frequencies of a periodic signal.
Debasis Kundu, Swagata Nandi
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In this section, we provide different estimation procedures of the frequencies of a periodic signal.
Debasis Kundu, Swagata Nandi
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Perceptual Frames in Frequency Estimation
Psychological Reports, 2014This study is an introductory investigation of cognitive frames, focused on perceptual frames divided into information and formal perceptual frames, which were studied based on sub-additivity of frequency estimations. It was postulated that different presentations of a response scale would result in different percentage estimates of time spent watching
Aleksandra, Zyłowska +2 more
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Journal of Applied Probability, 1973
Very general forms of the strong law of large numbers and the central limit theorem are proved for estimates of the unknown parameters in a sinusoidal oscillation observed subject to error. In particular when the unknown frequency θ0, is in fact 0 or <it is shown that the estimate, , satisfies for N ≧ N0 (ω) where N0 (ω) is an integer, determined ...
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Very general forms of the strong law of large numbers and the central limit theorem are proved for estimates of the unknown parameters in a sinusoidal oscillation observed subject to error. In particular when the unknown frequency θ0, is in fact 0 or <it is shown that the estimate, , satisfies for N ≧ N0 (ω) where N0 (ω) is an integer, determined ...
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Estimating the frequency of a periodic function
Biometrika, 1991SUMMARY The problem of estimating the frequency and other parameters of a cyclical oscillation is considered, where the data consists of a periodic function observed subject to stationary additive noise. An estimation procedure is proposed and the asymptotic properties of the estimators established.
B. G. Quinn, P. J. Thomson
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2012
Abstract Numerical methods have been used for fitting sinusoids to data since the middle of the 18th century. Since the discovery of the Fast Fourier Transform by Cooley and Tukey in 1965, the techniques for estimating frequency have become computationally feasible.
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Abstract Numerical methods have been used for fitting sinusoids to data since the middle of the 18th century. Since the discovery of the Fast Fourier Transform by Cooley and Tukey in 1965, the techniques for estimating frequency have become computationally feasible.
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