Search Results - "Walden, A. T."

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  1. 1

    Matrix-Valued and Quaternion Wavelets by Ginzberg, P., Walden, A. T.

    Published in IEEE transactions on signal processing (01-03-2013)
    “…Wavelet transforms using matrix-valued wavelets (MVWs) can process the components of vector-valued signals jointly. We construct some novel families of…”
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  2. 2

    A Statistical Study of Temporally Smoothed Wavelet Coherence by Cohen, E A K, Walden, A T

    Published in IEEE transactions on signal processing (01-06-2010)
    “…The use of the wavelet coherence of two series in hypothesis testing relies on some sort of smoothing being carried out in order that the coherence estimator…”
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  3. 3

    Testing for Quaternion Propriety by Ginzberg, P, Walden, A T

    Published in IEEE transactions on signal processing (01-07-2011)
    “…We consider the problem of testing whether a quaternion-valued Gaussian random vector is proper. The quaternion covariance matrix fully describes the…”
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  4. 4

    Generating Different Gaussian Multivariate Processes With Identical Graphs by Walden, A. T.

    Published in IEEE signal processing letters (2024)
    “…Graph learning from stationary multivariate time series typically involves hypothesis testing based on test statistics defined over the full frequency range or…”
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  5. 5

    Statistical Properties of the Estimator of the Rotary Coefficient by Chandna, S, Walden, A T

    Published in IEEE transactions on signal processing (01-03-2011)
    “…Rotary spectral analysis is a widely-used technique for studying elliptical motions in ocean currents, wind, etc. Statistical properties (distribution, bias,…”
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  6. 6

    The Hilbert spectrum via wavelet projections by Olhede, S., Walden, A. T.

    “…Non-stationary signals are increasingly analysed in the time-frequency domain to determine the variation of frequency components with time. It was recently…”
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  7. 7

    Wavelet Coherence for Certain Nonstationary Bivariate Processes by Cohen, E A K, Walden, A T

    Published in IEEE transactions on signal processing (01-06-2011)
    “…A previous study considered the estimation of wavelet coherence from jointly stationary time series via time-domain smoothing and use of a single Morlet…”
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  8. 8

    Tapering Promotes Propriety for Fourier Transforms of Real-Valued Time Series by Walden, A. T., Leong, Z.

    Published in IEEE transactions on signal processing (01-09-2018)
    “…We examine Fourier transforms of real-valued stationary time series from the point of view of the statistical propriety. Processes with a large dynamic range…”
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  9. 9

    A unified view of multitaper multivariate spectral estimation by Walden, A. T.

    Published in Biometrika (01-12-2000)
    “…The orthogonal multitaper framework for cross‐spectral estimators provides a simple unifying structure for determining the corresponding statistical…”
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  10. 10

    Correntropy: Implications of nonGaussianity for the moment expansion and deconvolution by Yang, Z., Walden, A.T., McCoy, E.J.

    Published in Signal processing (01-04-2011)
    “…The recently introduced correntropy function is an interesting and useful similarity measure between two random variables which has found myriad applications…”
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  11. 11

    Rotary components, random ellipses and polarization: a statistical perspective by Walden, A. T.

    “…Rotary analysis decomposes vector motions on the plane into counter-rotating components, which have proved particularly useful in the study of geophysical…”
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  12. 12

    Constructing brain connectivity group graphs from EEG time series by Walden, A. T., Zhuang, L.

    Published in Journal of applied statistics (26-04-2019)
    “…Graphical analysis of complex brain networks is a fundamental area of modern neuroscience. Functional connectivity is important since many neurological and…”
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  13. 13

    Quaternion VAR Modelling and Estimation by Ginzberg, P., Walden, A. T.

    Published in IEEE transactions on signal processing (01-01-2013)
    “…Quaternion vector autoregression (VAR) modeling is a natural extension of real and complex VAR. We demonstrate how a quaternion VAR can be treated as a special…”
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  14. 14

    Statistical Properties and Uses of the Wavelet Variance Estimator for the Scale Analysis of Time Series by Serroukh, A., Walden, A. T., Percival, D. B.

    “…Many physical processes are an amalgam of components operating on different scales, and scientific questions about observed data are often inherently linked to…”
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  15. 15

    Local directional denoising by Olhede, S.C., Walden, A.T.

    Published in IEEE transactions on signal processing (01-12-2005)
    “…Denoising of complex-valued signals involves the relationships between the real and imaginary parts of the signal. The authors introduce the idea of local…”
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  16. 16

    Simulation Methodology for Inference on Physical Parameters of Complex Vector-Valued Signals by Chandna, S., Walden, Andrew T.

    Published in IEEE transactions on signal processing (01-11-2013)
    “…Complex-valued vector time series occur in diverse fields such as oceanography and meteorology, and scientifically interpretable parameters may be estimated…”
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  17. 17

    From Blackman–Tukey pilot estimators to wavelet packet estimators: a modern perspective on an old spectrum estimation idea by Tsakiroglou, E., Walden, A.T.

    Published in Signal processing (01-10-2002)
    “…The ubiquitous problem of good spectrum estimation has been researched for many years, and in their seminal 1958 book Blackman and Tukey describe a ‘pilot…”
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  18. 18

    Graphical modelling for brain connectivity via partial coherence by Medkour, T., Walden, A.T., Burgess, A.

    Published in Journal of neuroscience methods (15-06-2009)
    “…Spectral and coherence methodologies are ubiquitous for the analysis of multiple time series. Partial coherence analysis may be used to try to determine…”
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  19. 19

    Wavelet analysis of matrix–valued time–series by Walden, A. T., Serroukh, A.

    “…The construction of matrix–valued filters for multi–resolution analysis of matrix–valued time–series is studied. Several different designs are explicitly…”
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  20. 20

    The phase–corrected undecimated discrete wavelet packet transform and its application to interpreting the timing of events by Walden, A. T., Cristan, A. Contreras

    “…The phase–corrected MODWPT is applied to a non–stationary time series of hourly averaged Southern Hemisphere solar magnetic field magnitude data acquired by…”
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