Results 1 to 10 of about 1,219,628 (202)

Hochschild Cohomology Theories in White Noise Analysis [PDF]

open access: yesSymmetry, Integrability and Geometry: Methods and Applications, 2008
We show that the continuous Hochschild cohomology and the differential Hochschild cohomology of the Hida test algebra endowed with the normalized Wick product are the same.
Rémi Léandre
doaj   +8 more sources

Deformation Quantization in White Noise Analysis [PDF]

open access: yesSymmetry, Integrability and Geometry: Methods and Applications, 2007
We define and present an example of a deformation quantization product on a Hida space of test functions endowed with a Wick product.
Rémi Léandre
doaj   +5 more sources

Model of the Signal of the Galileo Satellite Navigation System [PDF]

open access: yesTransNav, 2023
This article presents an analysis of the Galileo E1 signal and its sensitivity to different types of interference. The research involved modeling white noise, chaotic impulse interference, and narrowband interference and the effects of these interfering ...
Milan Džunda   +2 more
doaj   +1 more source

Dirichlet forms and white noise analysis [PDF]

open access: yesCommunications in Mathematical Physics, 1988
The framework of white noise analysis [\textit{T. Hida}, Brownian motion (1980; Zbl 0432.60002)] is used to construct and investigate Dirichlet forms [\textit{M. Fukushima}, Dirichlet forms and Markov processes. (1980; Zbl 0422.31007)] over \({\mathcal S}^*({\mathbb{R}})\) (the generalization of \({\mathcal S}^*({\mathbb{R}}^ d)\) being obvious). Let (\
HIDA, T, POTTHOFF, J, Streit, Ludwig
openaire   +3 more sources

Denoising Analysis of Partial Discharge Acoustic Signal Based on SVMD-PCA

open access: yesJournal of Applied Science and Engineering, 2023
Partial discharge (PD) acoustic signal detection is one of the effective means to assess the insulation status of power transformers. In actual monitoring, white noise is likely to cause strong interference to the partial discharge acoustic signal of the
Panpan Cao   +3 more
doaj   +1 more source

An empirical comparison of information-theoretic criteria in estimating the number of independent components of fMRI data. [PDF]

open access: yesPLoS ONE, 2011
BACKGROUND: Independent Component Analysis (ICA) has been widely applied to the analysis of fMRI data. Accurate estimation of the number of independent components of fMRI data is critical to reduce over/under fitting.
Mingqi Hui   +4 more
doaj   +1 more source

Weighted Local Times of a Sub-fractional Brownian Motion as Hida Distributions

open access: yesJurnal Matematika Integratif, 2020
The sub-fractional Brownian motion is a Gaussian extension of the Brownian motion. It has the properties of self-similarity, continuity of the sample paths, and short-range dependence, among others.
Herry Pribawanto Suryawan
doaj   +1 more source

Constant Resting Frequency and Auditory Midbrain Neuronal Frequency Analysis of Hipposideros pratti in Background White Noise

open access: yesFrontiers in Behavioral Neuroscience, 2021
Acoustic communication signals are inevitably challenged by ambient noise. In response to noise, many animals adjust their calls to maintain signal detectability.
Guimin Zhang   +8 more
doaj   +1 more source

Quantum Propagator Derivation for the Ring of Four Harmonically Coupled Oscillators

open access: yesJurnal Penelitian Fisika dan Aplikasinya, 2019
The ring model of the coupled oscillator has enormously studied from the perspective of quantum mechanics. The research efforts on this system contribute to fully grasp the concepts of energy transport, dissipation, among others, in mesoscopic and ...
James Mendoza Gallo   +1 more
doaj   +1 more source

On operators of stochastic differentiation on spaces of regular test and generalized functions of Lévy white noise analysis

open access: yesKarpatsʹkì Matematičnì Publìkacìï, 2014
The operators of stochastic differentiation, which are closely related with the extended Skorohod stochastic integral and with the Hida stochastic derivative, play an important role in the classical (Gaussian) white noise analysis.
M.M. Dyriv, N.A. Kachanovsky
doaj   +1 more source

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