Learning dynamics from nonstationary time series: Analysis of electroencephalograms

Gribkov, D. A.; Gribkova, V. V.

doi:10.1103/physreve.61.6538

Cited by 42 publications

(21 citation statements)

References 11 publications

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“…From the dynamical point of view, abnormality of cracks in concrete dams mainly means that the dam state in the phase space no longer tends to the original attractor but to a new one because of the evolution of internal dynamical structure or large external disturbance. In addition, it is generally supposed that a significant change in dynamical structures can be reflected in the observation sequence of relevant variables [10]. The exponent method of dynamical cross-correlation factor to diagnose abnormality of cracks in concrete dams is proposed based on the thought of exponent of dynamical correlation factor [11][12][13] in the paper.…”

Section: Abnormality Diagnosis Methods Of Cracks In Concrete Damsmentioning

confidence: 99%

Abnormality monitoring model of cracks in concrete dams

Bao

Dong

Zhou

et al. 2011

Sci. China Technol. Sci.

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The abnormality monitoring model (AMM) of cracks in concrete dams is established through integrating safety monitoring theories with abnormality diagnosis methods of cracks. In addition, emphasis is placed on the influence of crack depth on crack mouth opening displacement (CMOD). A linear hypothesis is proposed for the propagation process of cracks in concrete based on the fictitious crack model (FCM). Abnormality points are detected through testing methods of dynamical structure mutation and statistical model mutation. The solution of AMM is transformed into a global optimization problem, which is solved by the particle swarm optimization (PSO) method. Therefore, the AMM of cracks in concrete dams is established and solved completely. In the end of the paper, the proposed model is validated by a typical crack at the 105 m elevation of a concrete gravity arch dam.concrete dam, cracks, abnormality monitoring model, a linear hypothesis, abnormality diagnosis, particle swarm optimization method Citation:Bao T F, Qin D, Zhou X W, et al. Abnormality monitoring model of cracks in concrete dams.

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Section: Abnormality Diagnosis Methods Of Cracks In Concrete Damsmentioning

confidence: 99%

Abnormality monitoring model of cracks in concrete dams

Bao

Dong

Zhou

et al. 2011

Sci. China Technol. Sci.

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show abstract

“…The reason lies in the evolution of internal dynamical structure or large external disturbance. In addition, it is generally supposed that a significant change in dynamical structure can be reflected in the observed sequence of relevant variables [3]. Therefore, dynamical properties of the observed sequence can be used to analyze the dynamical behavior of an actual dam.…”

Section: Introductionmentioning

confidence: 99%

Abnormality diagnosis of cracks in the concrete dam based on dynamical structure mutation

2011

Sci. China Technol. Sci.

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A method of the fuzzy cross-correlation factor exponent in dynamics is researched and proposed to diagnose abnormality of cracks in the concrete dam. Moreover, the Logistic time series changing from period-doubling bifurcation to chaos is tested first using this method. Results indicate that it can distinguish inherent dynamics of time series and can detect mutations. Considering that cracks in the concrete dam constitute an open, dissipative and complex nonlinear dynamical system, a typical crack on the downstream face of a concrete gravity arch dam is analyzed with the proposed method. Two distinct mutations are discovered to indicate that the abnormality diagnosis of cracks in the concrete dam is achieved dynamically through this method. Furthermore, because it can be directly utilized in the measured crack opening displacement series to complete abnormality diagnosis, it has a good prospect for practical applications.dynamical structure mutation, cracks in the concrete dam, method of the fuzzy cross-correlation factor exponent in dynamics, abnormality diagnosis of cracks Citation:Gu C S, Li Z C, Xu B. Abnormality diagnosis of cracks in the concrete dam based on dynamical structure mutation.

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“…This type of analysis has been applied in several studies of EEG signals. For instance, quantitative characteristics of segmental organization of the brain signals were explored in resting state EEG [14], [15]. Another study reported differences in the duration of stationary EEG segments between patients with mild Alzheimer's disease and healthy subjects [16].…”

Section: Introductionmentioning

confidence: 99%

Exploring Age-Related Changes in Dynamical Non-Stationarity in Electroencephalographic Signals during Early Adolescence

et al. 2013

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Dynamics of brain signals such as electroencephalogram (EEG) can be characterized as a sequence of quasi-stable patterns. Such patterns in the brain signals can be associated with coordinated neural oscillations, which can be modeled by non-linear systems. Further, these patterns can be quantified through dynamical non-stationarity based on detection of qualitative changes in the state of the systems underlying the observed brain signals. This study explored age-related changes in dynamical non-stationarity of the brain signals recorded at rest, longitudinally with 128-channel EEG during early adolescence (10 to 13 years of age, 56 participants). Dynamical non-stationarity was analyzed based on segmentation of the time series with subsequent grouping of the segments into clusters with similar dynamics. Age-related changes in dynamical non-stationarity were described in terms of the number of stationary states and the duration of the stationary segments. We found that the EEG signal became more non-stationary with age. Specifically, the number of states increased whereas the mean duration of the stationary segment decreased with age. These two effects had global and parieto-occipital distribution, respectively, with the later effect being most dominant in the alpha (around 10 Hz) frequency band.

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Learning dynamics from nonstationary time series: Analysis of electroencephalograms

Cited by 42 publications

References 11 publications

Abnormality monitoring model of cracks in concrete dams

Abnormality monitoring model of cracks in concrete dams

Abnormality diagnosis of cracks in the concrete dam based on dynamical structure mutation

Exploring Age-Related Changes in Dynamical Non-Stationarity in Electroencephalographic Signals during Early Adolescence

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