Detecting nonstationarity and state transitions in a time series.
about
From phase space to frequency domain: a time-frequency analysis for chaotic time series.Research on zheng classification fusing pulse parameters in coronary heart disease.Phase coherence and attractor geometry of chaotic electrochemical oscillators.Classification of obsessive compulsive disorder by EEG complexity and hemispheric dependency measurements.Estimation and interpretation of 1/falpha noise in human cognitionFast monitoring of epileptic seizures using recurrence time statistics of electroencephalography.Distinguishing dynamics using recurrence-time statistics.Detecting dynamical changes in time series using the permutation entropy.Assessment of long-range correlation in time series: how to avoid pitfalls.Controlling chaos with weak periodic signals optimized by a genetic algorithm.Recurrence time statistics: versatile tools for genomic DNA sequence analysis.Lorenz-like systems and classical dynamical equations with memory forcing: an alternate point of view for singling out the origin of chaos.
P2860
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P2860
Detecting nonstationarity and state transitions in a time series.
description
2001 nî lūn-bûn
@nan
2001年の論文
@ja
2001年学术文章
@wuu
2001年学术文章
@zh
2001年学术文章
@zh-cn
2001年学术文章
@zh-hans
2001年学术文章
@zh-my
2001年学术文章
@zh-sg
2001年學術文章
@yue
2001年學術文章
@zh-hant
name
Detecting nonstationarity and state transitions in a time series.
@en
Detecting nonstationarity and state transitions in a time series.
@nl
type
label
Detecting nonstationarity and state transitions in a time series.
@en
Detecting nonstationarity and state transitions in a time series.
@nl
prefLabel
Detecting nonstationarity and state transitions in a time series.
@en
Detecting nonstationarity and state transitions in a time series.
@nl
P2860
P1433
P1476
Detecting nonstationarity and state transitions in a time series.
@en
P2093
P2860
P304
P356
10.1103/PHYSREVE.63.066202
P407
P433
P577
2001-05-11T00:00:00Z