Journal ArticleDOI
The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms
TLDR
In this article, the use of the fast Fourier transform in power spectrum analysis is described, and the method involves sectioning the record and averaging modified periodograms of the sections.Abstract:
The use of the fast Fourier transform in power spectrum analysis is described. Principal advantages of this method are a reduction in the number of computations and in required core storage, and convenient application in nonstationarity tests. The method involves sectioning the record and averaging modified periodograms of the sections.read more
Citations
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Journal ArticleDOI
Cognitive radio: brain-empowered wireless communications
TL;DR: Following the discussion of interference temperature as a new metric for the quantification and management of interference, the paper addresses three fundamental cognitive tasks: radio-scene analysis, channel-state estimation and predictive modeling, and the emergent behavior of cognitive radio.
Journal ArticleDOI
On the use of windows for harmonic analysis with the discrete Fourier transform
TL;DR: A comprehensive catalog of data windows along with their significant performance parameters from which the different windows can be compared is included, and an example demonstrates the use and value of windows to resolve closely spaced harmonic signals characterized by large differences in amplitude.
Journal ArticleDOI
Spectrum estimation and harmonic analysis
TL;DR: In this article, a local eigenexpansion is proposed to estimate the spectrum of a stationary time series from a finite sample of the process, which is equivalent to using the weishted average of a series of direct-spectrum estimates based on orthogonal data windows to treat both bias and smoothing problems.
Journal ArticleDOI
Spectrum analysis—A modern perspective
Steven Kay,S.L. Marple +1 more
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.
Book
Wavelet Methods for Time Series Analysis
TL;DR: Wavelet analysis of finite energy signals and random variables and stochastic processes, analysis and synthesis of long memory processes, and the wavelet variance.
References
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Journal ArticleDOI
Discussion, Emphasizing the Connection Between Analysis of Variance and Spectrum Analysis*
TL;DR: In this paper, a classical analysis of variance, based on a pattern involving d observations in each of the r.c cells formed by crossing r rows with c columns, is studied.
Journal ArticleDOI
A direct digital method of power spectrum estimation
TL;DR: A method of digital power spectrum estimation involving the direct combination of the sample time function with sines and cosines and the practical design details necessary for the planning of a spectral estimation program are treated.
Journal ArticleDOI
An exploratory study of the bi-spectrum of economic time series
TL;DR: In this paper, the authors present an analysis of the non-linear properties of the mechanism which may be used to generate a time series, specifically quadratic terms in the generating model.