Digital Bispectral Analysis and Its Applications to Nonlinear Wave Interactions
TL;DR: The bispectrum, which is an ensemble average of a product of three spectral components, is shown to be a very useful diagnostic tool in experimental studies of nonlinear wave interactions in random media.
Abstract: The bispectrum, which is an ensemble average of a product of three spectral components, is shown to be a very useful diagnostic tool in experimental studies of nonlinear wave interactions in random media. In particular, it is shown that the bicoherence spectrum may be used to discriminate between nonlinearly coupled waves and spontaneously excited waves and to measure the fraction of wave power due to the quadratic wave coupling in a self-excited fluctuation spectrum. Practical aspects of digital bispectral analysis techniques, such as estimation and statistical variability of the estimator, are also discussed. Finally, applications of bispectral analysis techniques in the analysis and interpretation of plasma fluctuation data are described.
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TL;DR: Quantification of ERD/ERS in time and space is demonstrated on data from a number of movement experiments, whereby either the same or different locations on the scalp can display ERD and ERS simultaneously.
6,093 citations
TL;DR: In this article, the authors reviewed different techniques, methodologies and algorithms developed to monitor the performance of wind turbine as well as for an early fault detection to keep away the wind turbines from catastrophic conditions due to sudden breakdowns.
Abstract: Renewable energy sources like wind energy are copiously available without any limitation. Wind turbines are used to tap the potential of wind energy, which is available in millions of MW. Reliability of wind turbine is critical to extract this maximum amount of energy from the wind. We reviewed different techniques, methodologies and algorithms developed to monitor the performance of wind turbine as well as for an early fault detection to keep away the wind turbines from catastrophic conditions due to sudden breakdowns. To keep the wind turbine in operation, implementation of condition monitoring system (CMS) and fault detection system (FDS) is paramount and for this purpose ample knowledge of these two types of systems is mandatory. So, an attempt has been made in this direction to review maximum approaches related to CMS and FDS in this piece of writing.
982 citations
Book•
01 Feb 2010TL;DR: The SWAN wave model as discussed by the authors is a wave model based on linear wave theory (SWAN) for oceanic and coastal waters, and it has been shown to be effective in detecting ocean waves.
Abstract: 1. Introduction 2. Observation techniques 3. Description of ocean waves 4. Statistics 5. Linear wave theory (oceanic waters) 6. Waves in oceanic waters 7. Linear wave theory (coastal waters) 8. Waves in coastal waters 9. The SWAN wave model Appendices References Index.
874 citations
Journal Article•
TL;DR: In this article, an internally or externally paced event results not only in the generation of an ERP but also in a change in the ongoing EEG/MEG in form of an event-related desynchronization (ERD) or eventrelated synchronization (ERS).
Abstract: An internally or externally paced event results not only in the generation of an event-related potential (ERP) but also in a change in the ongoing EEG/MEG in form of an event-related desynchronization (ERD) or event-related synchronization (ERS). The ERP on the one side and the ERD/ERS on the other side are different responses of neuronal structures in the brain. While the former is phase-locked, the latter is not phase-locked to the event. The most important difference between both phenomena is that the ERD/ERS is highly frequency bandspecific, whereby either the same or different locations on the scalp can display ERD and ERS simultaneously. Quantification of ERD/ERS in time and space is demonstrated on data from a number of movement experiments. q 1999 Elsevier Science Ireland Ltd. All rights reserved.
537 citations
TL;DR: The authors model a finite-dimensional system as an ARMA (autoregressive moving-average) rational function of known orders, but the special cases of AR, MA, and all-pass models are also considered.
Abstract: A method is presented for identification of linear, time-variant, nonminimum phase systems when only output data are available. The input sequence need not be independent, but it must be non-Gaussian, with some special properties described in the test. The authors model a finite-dimensional system as an ARMA (autoregressive moving-average) rational function of known orders, but the special cases of AR, MA, and all-pass models are also considered. To estimate the parameters of their model, the authors utilize both second- and higher-order statistics of the output, which may be contaminated by additive, zero-mean, Gaussian white noise of unknown variance. The parameter estimators obtained are proved, under mild conditions, to be consistent. Simulations verify the performance of the proposed method in the case of relatively low signal-to-noise ratios, and when there is a model-order mismatch. >
492 citations
References
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01 Jan 1978
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.
Abstract: This paper makes available a concise review of data windows and their affect on the detection of harmonic signals in the presence of broad-band noise, and in the presence of nearby strong harmonic interference. We also call attention to a number of common errors in the application of windows when used with the fast Fourier transform. This paper includes a comprehensive catalog of data windows along with their significant performance parameters from which the different windows can be compared. Finally, an example demonstrates the use and value of windows to resolve closely spaced harmonic signals characterized by large differences in amplitude.
7,130 citations
197 citations
"Digital Bispectral Analysis and Its..." refers methods in this paper
...By properly implementing linear spectral analysis techniques, it is feasible to study fluctuation-induced transport in plasmas [4] and a recent experiment has successfully shown the usefulness of the technique [5]....
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TL;DR: In this article, several basic power-spectrum estimation procedures are reviewed and their statistical and mathematical properties are discussed and compared with the standard procedure that uses the cosine transform of the estimated correlation function.
Abstract: The computation of power spectra, cross spectra, coherence, and bispectra of various types of geophysical random processes is part of the established routine. Since it is routine, some of the standard procedures need to be examined rather carefully to be certain that the assumptions behind the procedures are applicable to the data on hand. The basic criteria for a particular method are its resolution bandwidth, its variance, and its bias. In this paper several basic power-spectrum estimation procedures are reviewed and their statistical and mathematical properties are discussed. The direct use of the discrete Fourier transform for various spectrum calculations is discussed in detail, and its properties are compared with the standard procedure that uses the cosine transform of the estimated correlation function.
166 citations
TL;DR: In this article, a bispectral analysis is used to distinguish between spontaneously excited modes and coupled modes in a self-excited fluctuation spectrum by measuring the degree of phase coherence between the interacting waves.
Abstract: Digitally implemented bispectral analysis is used to distinguish between spontaneously excited modes and coupled modes in a self‐excited fluctuation spectrum by measuring the degree of phase coherence between the interacting waves.
139 citations
TL;DR: In this article, a bispectral analysis of high Reynolds number turbulent velocity-derivative data is carried out and it is shown that the contributions of wavenumber triplets to the rate of vorticity production and spectral transfer are non-local in the wenumber space and comparable over the whole range of wenumbers studied.
Abstract: A bispectral analysis of high Reynolds number turbulent velocity-derivative data is carried out. The computations suggest that contributions of wavenumber triplets to the rate of vorticity production and spectral transfer are non-local in wavenumber space and comparable over the whole range of wavenumbers studied. Statistical resolvability of the bispectral estimates is obtained. An appendix on the asymptotic behaviour of bispectral estimates is given.
104 citations