Výsledky vyhledávání - "B. Cooper Boniece"

On operator fractional Lévy motion: integral representations and time-reversibility

Autor: B. Cooper Boniece, Gustavo Didier

Publikováno v: Advances in Applied Probability. 54:493-535

In this paper, we construct operator fractional Lévy motion (ofLm), a broad class of infinitely divisible stochastic processes that are covariance operator self-similar and have wide-sense stationary increments. The ofLm class generalizes the univar

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6eb387180a8948e738028bc1aec1a423
https://doi.org/10.1017/apr.2021.41

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On Fractional Lévy Processes: Tempering, Sample Path Properties and Stochastic Integration

Autor: B. Cooper Boniece, Gustavo Didier, Farzad Sabzikar

Publikováno v: Journal of Statistical Physics. 178:954-985

We define two new classes of stochastic processes, called tempered fractional Levy process of the first and second kinds (TFLP and TFLP II, respectively). TFLP and TFLP II make up very broad finite-variance, generally non-Gaussian families of transie

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3d34e2e0a2b07d5dcc0f9c0185698907
https://doi.org/10.1007/s10955-019-02475-1

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Wavelet eigenvalue regression in high dimensions

Autor: Patrice Abry, B. Cooper Boniece, Gustavo Didier, Herwig Wendt

Publikováno v: Statistical Inference for Stochastic Processes
Statistical Inference for Stochastic Processes, 2022, pp.1-33. ⟨10.1007/s11203-022-09279-3⟩

In this paper, we construct the wavelet eigenvalue regression methodology in high dimensions. We assume that possibly non-Gaussian, finite-variance $p$-variate measurements are made of a low-dimensional $r$-variate ($r \ll p$) fractional stochastic p

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::46ca388fbc71636e96f2950196680602
https://hal.science/hal-03850430/file/2108.03770.pdf

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Wavelet-Based Detection and Estimation of Fractional Lévy Signals in High Dimensions

Autor: Patrice Abry, Gustavo Didier, Herwig Wendt, B. Cooper Boniece

Publikováno v: Proceedings of CAMSAP 2019
IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2019)
IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2019), IEEE, Dec 2019, Guadeloupe, France. ⟨10.1109/CAMSAP45676.2019.9022442⟩
CAMSAP

International audience; In the modern world, systems are routinely monitored by multiple sensors, generating "Big Data" in the form of a large collection of time series. However, dynamic signals are often low-dimensional and characterized by joint sc

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f30d249d7ba01a7aa8d10525ee9bdf94
https://hal-cnrs.archives-ouvertes.fr/hal-03034138

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ON MULTIVARIATE NON-GAUSSIAN SCALE INVARIANCE: FRACTIONAL LÉVY PROCESSES AND WAVELET ESTIMATION

Autor: Patrice Abry, Gustavo Didier, B. Cooper Boniece, Herwig Wendt

Publikováno v: European Signal Processing Conference (EUSIPCO)
European Signal Processing Conference (EUSIPCO), Sep 2019, A Coruna, Spain
EUSIPCO

International audience; In the modern world of "Big Data," dynamic signals are often multivariate and characterized by joint scale-free dynamics (self-similarity) and non-Gaussianity. In this paper, we examine the performance of joint wavelet eigenan

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::908884b5fbbdcc3970035b4dfdad5883
https://hal.science/hal-02361748/document

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Tempered fractional Brownian motion: wavelet estimation, modeling and testing

Autor: Farzad Sabzikar, Gustavo Didier, B. Cooper Boniece

The Davenport spectrum is a modification of the classical Kolmogorov spectrum for the inertial range of turbulence that accounts for non-scaling low frequency behavior. Like the classical fractional Brownian motion vis-\`a-vis the Kolmogorov spectrum

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d1c6948f41e872a303d15b6eb18e3297
http://arxiv.org/abs/1808.04935

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