The Estimation and Tracking of Frequency

Overview

Many electronic and acoustic signals can be modeled as sums of sinusoids and noise. However, the amplitudes, phases and frequencies of the sinusoids are often unknown and must be estimated in order to characterize the periodicity or near-periodicity of a signal and consequently to identify its source. Quinn and Hannan present and analyze several practical techniques used for such estimation. The problem of tracking slow frequency changes of a very noisy sinusoid over time is also considered. Rigorous analyses are...
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Overview

Many electronic and acoustic signals can be modeled as sums of sinusoids and noise. However, the amplitudes, phases and frequencies of the sinusoids are often unknown and must be estimated in order to characterize the periodicity or near-periodicity of a signal and consequently to identify its source. Quinn and Hannan present and analyze several practical techniques used for such estimation. The problem of tracking slow frequency changes of a very noisy sinusoid over time is also considered. Rigorous analyses are presented via asymptotic or large sample theory, together with physical insight. The book focuses on achieving extremely accurate estimates when the signal to noise ratio is low but the sample size is large.
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Editorial Reviews

From the Publisher
"This book...can be useful to both statisticians and signal processing people." Pham Dinh Tuan, Mathematical Reviews

"The book does what it sets out to do, and by restricting its scope, is able to focus in-depth on specific aspects of the problem...This book fulfils a role I think primarily as a high-quality expository monograph...It is a nicely presented exposition of one strand of the frequency estimation story, and it is pleasing to see a book devoted to this subject." International Journal of Robust and Nonlinear Control

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Product Details

Table of Contents

Preface; 1. Introduction; 2. Statistical and probabilistic methods; 3. The estimation of a fixed frequency; 4. Techniques derived from ARMA modelling; 5. Estimation using Fourier coefficients; 6. Tracking frequency in low SNR conditions; 7. Other estimation techniques; References; Appendix. Matlab programs; Author index; Subject index.
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