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Journal ArticleDOI

Maximum entropy spectral estimation using the analytical signal

Steven Kay
- 01 Oct 1978 - 
- Vol. 26, Iss: 5, pp 467-469
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TLDR
Using maximum entropy power spectral estimation, the estimate of the frequency of a sinusoid in white noise has been shown to be very sensitive to the initial sinusoidal phase as discussed by the authors, which can be reduced by replacing the real data by its analytic form, reducing the sampling rate by two, and employing the power spectral estimate for complex data.
Abstract
Using maximum entropy power spectral estimation, the estimate of the frequency of a sinusoid in white noise has been shown to be very sensitive to the initial sinusoidal phase. This phase dependence can be significantly reduced by replacing the real data by its analytic form, reducing the sampling rate by two, and employing the power spectral estimate for complex data.

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Citations
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Journal ArticleDOI

Spectrum analysis—A modern perspective

TL;DR: In this paper, a summary of many of the new techniques developed in the last two decades for spectrum analysis of discrete time series is presented, including classical periodogram, classical Blackman-Tukey, autoregressive (maximum entropy), moving average, autotegressive-moving average, maximum likelihood, Prony, and Pisarenko methods.
Journal ArticleDOI

Computing the discrete-time "analytic" signal via FFT

TL;DR: Starting with a real-valued N-point discrete-time signal, frequency-domain algorithms are provided for computing the complex-valued standard N- point discrete time 'analytic' signal of the same sample rate.
Proceedings ArticleDOI

Computing the discrete-time 'analytic' signal via FFT

S.L. Marple
TL;DR: Starting with a real-valued N-point discrete-time signal, frequency-domain algorithms are provided for computing the complex-valued standard N- point discrete time 'analytic' signal of the same sample rate.
Journal ArticleDOI

A parameter estimation approach to estimation of frequencies of sinusoids

TL;DR: In this paper, it was shown that with uniform sampling, a sample of the sum of M sinusoids at time nT can be uniquely expressed as a linear combination of the 2M samples at times (n − 1)T,..., (n - 2M)T.
Journal ArticleDOI

The statistical performance of some instantaneous frequency estimators

TL;DR: The authors obtain the parabolic SCFD (PSCFD) estimator, which is unbiased and has a frequency-independent variance, yet retains the optimal performance and simplicity of the original estimator.
References
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Journal ArticleDOI

Data adaptive spectral analysis methods

R. T. Lacoss
- 01 Aug 1971 - 
TL;DR: In this paper, two new methods (Maximum Likelihood Method or MLM, and Maximum Entropy Method or MEM) for power spectral density estimation have been experimentally investigated, and both methods adapt to the actual characteristics of the noise process under study.
Journal ArticleDOI

Time series modelling and maximum entropy

TL;DR: In this article, the authors briefly review the principles of maximum entropy spectral analysis and the closely related problem of autoregressive time series modelling and discuss the important aspect of model identification.
Journal ArticleDOI

Experiments with maximum entropy power spectra of sinusoids

TL;DR: In this paper, the authors applied the maximum entropy technique to the estimation of power spectra of short sinusoids and found that the estimated spectral maximum was found to shift in relation to the true maximum.
Journal ArticleDOI

On the behavior of minimax fir digital Hilbert transformers

TL;DR: In this paper, the authors present useful design data on wideband Hilbert transformers with even and odd values of N, the impulse response duration (in samples) of the filter.
Proceedings ArticleDOI

Frequency estimation by linear prediction

TL;DR: It is shown that improved performance is obtained by processing a complex-valued version of the real-valued input signal, with the corresponsing sampling rate reduced by one-half, in the case of a single sinusoid in white noise.