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Generalized Mehler Semigroup on White Noise Functionals and White Noise Evolution Equations
Published 2020-06-01Subjects: “…white noise theory…”
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Hochschild Cohomology Theories in White Noise Analysis
Published 2008-09-01Subjects: “…white noise analysis…”
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White-noise fluctuation theorem for Langevin dynamics
Published 2022-01-01“…In this work, we introduce a detailed FT for Langevin dynamics that follows from the statistics of Gaussian white noise rather than from time-reversal. The theorem, which originates from a point-wise symmetry in phase space, holds individually for each degree of freedom coupled to additive or multiplicative noise. …”
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Stochastic Wiener filter in the white noise space
Published 2020-04-01Subjects: Get full text
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On Solvable Lie Algebras of White Noise Operators
Published 2022-11-01Subjects: “…white noise analysis…”
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Postmodern apocalypse in White Noise and London Fields
Published 2016“…This study analyzes postmodern apocalypse in two selected novels, namely Don DeLillo’s White Noise (1985) and Martin Amis’s London Fields (1989). …”
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Distillation of power in Don Delillo's White Noise
Published 2012“…(White Noise, 321).…”
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Differential effects of white noise in cognitive and perceptual tasks
Published 2015-11-01“…These results suggest that white noise has no general effect on cognitive functions. …”
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Luminance white noise electroretinograms (wnERGs) in mice
Published 2022-12-01Subjects: Get full text
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Stiff oscillatory systems, delta jumps and white noise
Published 1998“…The convergence of the algorithms is studied in this case in the limit of N tending to infinity and the time step tending to zero. For the white noise problem both strong and weak convergence are considered.…”
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Stiff Oscillatory Systems, Delta Jumps and White Noise.
Published 2001“…The convergence of the algorithms is studied in this case in the limit N → ∞ and Δt → 0. For the white noise problem both strong and weak convergence are considered. …”
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Validation of combine white noise using simulated data
Published 2016“…Recent studies reveal that the data that exhibits heteroscedasticity are modelled by Exponential Generalized Autoregressive Conditional Heteroscedastic (EGARCH).Nevertheless, EGARCH model estimation is not efficient when the heteroscedasticity data have leverage effect.In this study, an algorithm is developed which is called Combine White Noise (CWN).The standardized residuals of EGARCH errors (heteroscedastic variance) are decomposed into equal variances (white noise series). …”
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