Waveform-Aligned Adaptive Windows for Spectral Component Tracking and Noise Rejection

2014 ◽  
pp. 463-480 ◽  
Author(s):  
Yang Zhao ◽  
David Gerhard
Keyword(s):  
Spectral Component ◽  
Noise Rejection

Spectral and Topographic Microstructure of Brain Alpha Activity During Drowsiness at Sleep Onset and REM Sleep

2000 ◽  
Vol 14 (3) ◽  
pp. 151-158 ◽  
Author(s):  
José Luis Cantero ◽  
Mercedes Atienza
Keyword(s):  
Rem Sleep ◽  
Spectral Component ◽  
Sleep Onset ◽  
Quantitative Information ◽  
Maximum Energy ◽  
Alpha Activity ◽  
The Other ◽  
Classification Algorithms ◽  
Microstructural Properties ◽  
Brain States

Abstract High-resolution frequency methods were used to describe the spectral and topographic microstructure of human spontaneous alpha activity in the drowsiness (DR) period at sleep onset and during REM sleep. Electroencephalographic (EEG), electrooculographic (EOG), and electromyographic (EMG) measurements were obtained during sleep in 10 healthy volunteer subjects. Spectral microstructure of alpha activity during DR showed a significant maximum power with respect to REM-alpha bursts for the components in the 9.7-10.9 Hz range, whereas REM-alpha bursts reached their maximum statistical differentiation from the sleep onset alpha activity at the components between 7.8 and 8.6 Hz. Furthermore, the maximum energy over occipital regions appeared in a different spectral component in each brain activation state, namely, 10.1 Hz in drowsiness and 8.6 Hz in REM sleep. These results provide quantitative information for differentiating the drowsiness alpha activity and REM-alpha by studying their microstructural properties. On the other hand, these data suggest that the spectral microstructure of alpha activity during sleep onset and REM sleep could be a useful index to implement in automatic classification algorithms in order to improve the differentiation between the two brain states.

Performance of a neuro-model-based robot controller: adaptability and noise rejection

1992 ◽  
Vol 1 (1) ◽  
pp. 50 ◽  
Author(s):  
A.N. Poo ◽  
M.H. Ang ◽  
C.L. Teo ◽  
Qing Li
Keyword(s):  
Robot Controller ◽  
Model Based ◽  
Noise Rejection

scholarly journals Searching for energy-resolved quasi-periodic oscillations in AGN

2021 ◽  
Author(s):  
Dominic I Ashton ◽  
Matthew J Middleton
Keyword(s):  
Power Law ◽  
Spectral Component ◽  
Broad Band ◽  
Initial Study ◽  
Periodic Oscillations ◽  
Single Observation ◽  
Curved Space ◽  
Multiple Observations ◽  
Band Noise ◽  
The Impact

Abstract X-ray quasi-periodic oscillations (QPOs) in AGN allow us to probe and understand the nature of accretion in highly curved space-time, yet the most robust form of detection (i.e. repeat detections over multiple observations) has been limited to a single source to-date, with only tentative claims of single observation detections in several others. The association of those established AGN QPOs with a specific spectral component has motivated us to search the XMM-Newton archive and analyse the energy-resolved lightcurves of 38 bright AGN. We apply a conservative false alarm testing routine folding in the uncertainty and covariance of the underlying broad-band noise. We also explore the impact of red-noise leak and the assumption of various different forms (power-law, broken power-law and lorentzians) for the underlying broad-band noise. In this initial study, we report QPO candidates in 6 AGN (7 including one tentative detection in MRK 766) from our sample of 38, which tend to be found at characteristic energies and, in four cases, at the same frequency across at least two observations, indicating they are highly unlikely to be spurious in nature.

Exploring directionality in spontaneous heart period and systolic pressure variability interactions in humans: implications in the evaluation of baroreflex gain

2005 ◽  
Vol 288 (4) ◽  
pp. H1777-H1785 ◽  
Author(s):  
Giandomenico Nollo ◽  
Luca Faes ◽  
Alberto Porta ◽  
Renzo Antolini ◽  
Flavia Ravelli
Keyword(s):  
Spectral Analysis ◽  
Spectral Component ◽  
Systolic Pressure ◽  
Low Frequency ◽  
Systolic Arterial Pressure ◽  
Phase Lag ◽  
Healthy Humans ◽  
Head Up Tilt ◽  
Causal Approach ◽  
Young Subjects

Although in physiological conditions RR interval and systolic arterial pressure (SAP) are likely to interact in a closed loop, the traditional cross-spectral analysis cannot distinguish feedback (FB) from feedforward (FF) influences. In this study, a causal approach was applied for calculating the coherence from SAP to RR ( Ks-r) and from RR to SAP ( Kr-s) and the gain and phase of the baroreflex transfer function. The method was applied, compared with the noncausal one, to RR and SAP series taken from 15 healthy young subjects in the supine position and after passive head-up tilt. For the low frequency (0.04–0.15 Hz) spectral component, the enhanced FF coupling ( Kr-s = 0.59 ± 0.21, significant in 14 subjects) and the blunted FB coupling ( Ks-r = 0.17 ± 0.17, significant in 4 subjects) found at rest indicated the prevalence of nonbaroreflex mechanisms. The tilt maneuver recovered FB influences ( Ks-r = 0.47 ± 0.16, significant in 14 subjects), which were stronger than FF interactions ( Ks-r = 0.34 ± 0.19, significant in 9 subjects). At the respiratory frequency, the RR-SAP regulation was balanced at rest ( Ks-r = 0.30 ± 0.18 and Kr-s = 0.29 ± 0.20, significant in 11 and 8 subjects) and shifted toward FB mechanisms after tilt ( Ks-r = 0.35 ± 0.19 and Kr-s = 0.19 ± 0.11, significant in 14 and 8 subjects). The causal baroreflex gain estimates were always lower than the corresponding noncausal values and decreased significantly from rest to tilt in both frequency bands. The tilt-induced increase of the phase lag from SAP to RR suggested a shift from vagal to sympathetic modulation. Thus the importance of nonbaroreflex interactions pointed out the necessity of accounting for causality in the cross-spectral analysis of the interactions between cardiovascular variables in healthy humans.

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