Results 161 to 170 of about 17,761 (290)
Uniform bounds for the bilinear Hilbert transforms, I [PDF]
, 2004 Loukas Grafakos, Xiaochun Li
openalex +1 more source
Journal of Sleep Research, Volume 34, Issue 2, April 2025.Summary Boosting slow‐wave activity (SWA) by modulating slow waves through closed‐loop auditory stimulation (CLAS) might provide a powerful non‐pharmacological tool to investigate the link between sleep and neurodegeneration. Here, we established mouse CLAS (mCLAS)‐mediated SWA enhancement and explored its effects on sleep deficits in neurodegeneration,
Inês Dias +5 more
wiley +1 more source
PET and MRI image fusion based on combination of 2-D Hilbert transform and IHS method. [PDF]
Biomed J, 2017 Haddadpour M, Daneshvar S, Seyedarabi H.
europepmc +1 more source
NREM Sleep Oscillations Are Associated With Anxiety and Negative Affect in Young Adults
Journal of Sleep Research, EarlyView.ABSTRACT Non‐rapid eye movement sleep (NREM) oscillations are critical for cognitive and affective processing. While several studies link anxiety and depression symptoms to sleep quality, a critical gap remains in elucidating the role of NREM physiology in sleep‐dependent processing of affect and anxiety symptoms. The goals of the present study were to
Hazal Arpaci +5 more
wiley +1 more source
Long‐Term Visual Gist Abstraction Independent of Post‐Encoding Sleep
Journal of Sleep Research, EarlyView.ABSTRACT Current theories of memory processing postulate a slow transformation from episodic to abstract, gist‐like memories. We previously demonstrated that sleep shortly after learning improves gist abstraction in healthy volunteers across a one‐year retention interval using a visual version of the Deese‐Roediger‐McDermott (DRM) paradigm.
Nicolas D. Lutz +7 more
wiley +1 more source
The Stein–Weiss theorem for the ergodic Hilbert transform [PDF]
, 2004 Lasha Ephremidze
openalex +1 more source
Monitoring panels of sparse functional data
Journal of Time Series Analysis, EarlyView.Panels of random functions are common in applications of functional data analysis. They often occur when sequences of functions are observed at a number of different locations. We propose a methodology to monitor for structural breaks in such panels and to identify the changing components with statistical certainty.
Tim Kutta +2 more
wiley +1 more source
Change Point Analysis for Functional Data Using Empirical Characteristic Functionals
Journal of Time Series Analysis, EarlyView.ABSTRACT We develop a new method to detect change points in the distribution of functional data based on integrated CUSUM processes of empirical characteristic functionals. Asymptotic results are presented under conditions allowing for low‐order moments and serial dependence in the data establishing the limiting null‐distribution of the proposed test ...
Lajos Horváth +2 more
wiley +1 more source