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Detrended cross-correlation analysis of electroencephalogram 被引量:5
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作者 Wang Jun Zhao Da-Qing 《Chinese Physics B》 SCIE EI CAS CSCD 2012年第2期577-580,共4页
In the paper we use detrended cross-correlation analysis (DCCA) to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads o... In the paper we use detrended cross-correlation analysis (DCCA) to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads of a healthy young subject is larger than that of a healthy old subject. It was shown that the cross-correlation relationship decreases with the aging process and the phenomenon can help to diagnose whether the subject's brain function is healthy or not. 展开更多
关键词 detrended cross-correlation analysis ELECTROENCEPHALOGRAM brain function aging process
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Temporal-spatial cross-correlation analysis of non-stationary near-surface wind speed time series 被引量:3
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作者 ZENG Ming LI Jing-hai +1 位作者 MENG Qing-hao ZHANG Xiao-nei 《Journal of Central South University》 SCIE EI CAS CSCD 2017年第3期692-698,共7页
Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time se... Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time series recorded at different locations are studied using the detrended fluctuation analysis(DFA),and the corresponding scaling exponents are larger than 1.This indicates that all these wind speed time series have non-stationary characteristics.Secondly,concerning this special feature( i.e.,non-stationarity)of wind signals,a cross-correlation analysis method,namely detrended cross-correlation analysis(DCCA) coefficient,is employed to evaluate the temporal-spatial cross-correlations between non-stationary time series of different anemometer pairs.Finally,experiments on ten wind speed data synchronously collected by the ten anemometers with equidistant arrangement illustrate that the method of DCCA cross-correlation coefficient can accurately analyze full-scale temporal-spatial cross-correlation between non-stationary time series and also can easily identify the seasonal component,while three traditional cross-correlation techniques(i.e.,Pearson coefficient,cross-correlation function,and DCCA method) cannot give us these information directly. 展开更多
关键词 temporal-spatial cross-correlation near-surface wind speed time series detrended cross-correlation analysis (DCCA) cross-correlation coefficient Pearson coefficient cross-correlation function
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New seismic attribute:Fractal scaling exponent based on gray detrended fluctuation analysis 被引量:1
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作者 黄亚平 耿建华 郭彤楼 《Applied Geophysics》 SCIE CSCD 2015年第3期343-352,467,共11页
Seismic attributes have been widely used in oil and gas exploration and development. However, owing to the complexity of seismic wave propagation in subsurface media, the limitations of the seismic data acquisition sy... Seismic attributes have been widely used in oil and gas exploration and development. However, owing to the complexity of seismic wave propagation in subsurface media, the limitations of the seismic data acquisition system, and noise interference, seismic attributes for seismic data interpretation have uncertainties. Especially, the antinoise ability of seismic attributes directly affects the reliability of seismic interpretations. Gray system theory is used in time series to minimize data randomness and increase data regularity. Detrended fluctuation analysis (DFA) can effectively reduce extrinsic data tendencies. In this study, by combining gray system theory and DFA, we propose a new method called gray detrended fluctuation analysis (GDFA) for calculating the fractal scaling exponent. We consider nonlinear time series generated by the Weierstrass function and add random noise to actual seismic data. Moreover, we discuss the antinoise ability of the fractal scaling exponent based on GDFA. The results suggest that the fractal scaling exponent calculated using the proposed method has good antinoise ability. We apply the proposed method to 3D poststack migration seismic data from southern China and compare fractal scaling exponents calculated using DFA and GDFA. The results suggest that the use of the GDFA-calculated fractal scaling exponent as a seismic attribute can match the known distribution of sedimentary facies. 展开更多
关键词 Seismic attribute gray system theory detrended fluctuation analysis fractal scaling exponent
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Relationships of exponents in multifractal detrended fluctuation analysis and conventional multifractal analysis 被引量:2
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作者 周煜 梁怡 喻祖国 《Chinese Physics B》 SCIE EI CAS CSCD 2011年第9期98-106,共9页
Multifractal detrended fluctuation analysis (MF-DFA) is a relatively new method of multifractal analysis. It is extended from detrended fluctuation analysis (DFA), which was developed for detecting the long-range ... Multifractal detrended fluctuation analysis (MF-DFA) is a relatively new method of multifractal analysis. It is extended from detrended fluctuation analysis (DFA), which was developed for detecting the long-range correlation and the fractal properties in stationary and non-stationary time series. Although MF-DFA has become a widely used method, some relationships among the exponents established in the original paper seem to be incorrect under the general situation. In this paper, we theoretically and experimentally demonstrate the invalidity of the expression r(q) = qh(q) - 1 stipulating the relationship between the multifractal exponent T(q) and the generalized Hurst exponent h(q). As a replacement, a general relationship is established on the basis of the universal multifractal formalism for the stationary series as .t-(q) = qh(q) - qH - 1, where H is the nonconservation parameter in the universal multifractal formalism. The singular spectra, a and f(a), are also derived according to this new relationship. 展开更多
关键词 fractals Hurst exponent multifractal detrended fluctuation analysis time series analysis
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Detrended Fluctuation Analysis on Correlations of Complex Networks Under Attack and Repair Strategy 被引量:4
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作者 CHI Li-Ping YANG Chun-Bin MAKe CAI Xu 《Communications in Theoretical Physics》 SCIE CAS CSCD 2006年第4期765-768,共4页
We analyze the correlation properties of the Erd6s-Rdnyi random graph (RG) and the Barabdsi-Albert scale-free network (SF) under the attack and repair strategy with detrended fluctuation analysis (DFA). The maxi... We analyze the correlation properties of the Erd6s-Rdnyi random graph (RG) and the Barabdsi-Albert scale-free network (SF) under the attack and repair strategy with detrended fluctuation analysis (DFA). The maximum degree kmax, representing the local property of the system, shows similar scaling behaviors for random graphs and scale-free networks. The fluctuations are quite random at short time scales but display strong anticorrelation at longer time scales under the same system size N and different repair probability pre. The average degree 〈k〉, revealing the statistical property of the system, exhibits completely different scaling behaviors for random graphs and scale-free networks. Random graphs display long-range power-law correlations. Scale-free networks are uncorrelated at short time scales; while anticorrelated at longer time scales and the anticorrelation becoming stronger with the increase of pre. 展开更多
关键词 CORRELATIONS detrended fluctuation analysis complex networks
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Extracting a seizure intensity index from one-channel EEG signal using bispectral and detrended fluctuation analysis 被引量:4
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作者 Pegah Tayaranian Hosseini Reza Shalbaf Ali Motie Nasrabadi 《Journal of Biomedical Science and Engineering》 2010年第3期253-261,共9页
Epilepsy is a medical condition that produces seizures affecting a variety of mental and physical functions. Seizures can last from a few seconds to a few minutes. They can have many symptoms, from convulsions and los... Epilepsy is a medical condition that produces seizures affecting a variety of mental and physical functions. Seizures can last from a few seconds to a few minutes. They can have many symptoms, from convulsions and loss of consciousness to blank staring, lip smacking, or jerking movements of arms and legs. If early warning signals of an upcoming seizure (diagnosis of preictal period) are detected, proper treatment can be applied to the patient to help prevent the seizure. In this research, an epileptic disorder has been divided into three subsets: Normal, Preictal (just before the seizure), and Ictal (during seizure). By using Detrended Fluctuation Analysis (DFA), Bispectral Analysis (BIS), and Standard Deviation (SD) three features from single-channel EEG signals have been derived in the foresaid groups. A fuzzy classifier is used to separate the three groups which can successfully separate them with a separation degree of 100% and further a fuzzy inference engine is used to extract a Seizure Intensity Index (SII) from the Electroencephalogram (EEG) signals of the three different states. One can apparently see the distinction of SII amounts between the three states. It is more important when one remembers that these results are just from single-channel EEG signal. 展开更多
关键词 EPILEPSY Fuzzy INFERENCE Engine BISPECTRUM detrended FLUCTUATION analysis
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Correlation between detrended fluctuation analysis and the Lempel-Ziv complexity in nonlinear time series analysis 被引量:1
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作者 唐友福 刘树林 +1 位作者 姜锐红 刘颖慧 《Chinese Physics B》 SCIE EI CAS CSCD 2013年第3期219-225,共7页
We study the correlation between detrended fluctuation analysis(DFA) and the Lempel-Ziv complexity(LZC) in nonlinear time series analysis in this paper.Typical dynamic systems including a logistic map and a Duffin... We study the correlation between detrended fluctuation analysis(DFA) and the Lempel-Ziv complexity(LZC) in nonlinear time series analysis in this paper.Typical dynamic systems including a logistic map and a Duffing model are investigated.Moreover,the influence of Gaussian random noise on both the DFA and LZC are analyzed.The results show a high correlation between the DFA and LZC,which can quantify the non-stationarity and the nonlinearity of the time series,respectively.With the enhancement of the random component,the exponent α and the normalized complexity index C show increasing trends.In addition,C is found to be more sensitive to the fluctuation in the nonlinear time series than α.Finally,the correlation between the DFA and LZC is applied to the extraction of vibration signals for a reciprocating compressor gas valve,and an effective fault diagnosis result is obtained. 展开更多
关键词 nonlinear time series detrended fluctuation analysis Lempel-Ziv complexity correlation coefficient
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Detrended Fluctuation Analysis of the Human EEG during Listening to Emotional Music 被引量:2
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作者 Ting-Ting Gao Dan Wu Ying-Ling Huang De-Zhong Yao 《Journal of Electronic Science and Technology of China》 2007年第3期272-277,共6页
A nonlinear method named detrended fluctuation analysis (DFA) was utilized to investigate the scaling behavior of the human electroencephalogram (EEG) in three emotional music conditions (fear, happiness, sadness... A nonlinear method named detrended fluctuation analysis (DFA) was utilized to investigate the scaling behavior of the human electroencephalogram (EEG) in three emotional music conditions (fear, happiness, sadness) and a rest condition (eyes-closed). The results showed that the EEG exhibited scaling behavior in two regions with two scaling exponents β1 and β2 which represented the complexity of higher and lower frequency activity besides α band respectively. As the emotional intensity decreased the value of β1 increased and the value of β2 decreased. The change of β1 was weakly correlated with the 'approach-withdrawal' model of emotion and both of fear and sad music made certain differences compared with the eyes-closed rest condition. The study shows that music is a powerful elicitor of emotion and that using nonlinear method can potentially contribute to the investigation of emotion. 展开更多
关键词 detrended fluctuation analysis (DFA) electroencephalogram(EEG) EMOTION MUSIC scaling.
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A Multifractal Detrended Fluctuation Analysis of the Ising Financial Markets Model with Small World Topology 被引量:1
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作者 张昂辉 李晓温 +1 位作者 苏桂锋 张一 《Chinese Physics Letters》 SCIE CAS CSCD 2015年第9期13-16,共4页
We present a multifractal detrended fluctuation analysis (MFDFA) of the time series of return generated by our recently-proposed Ising financial market model with underlying small world topology. The result of the M... We present a multifractal detrended fluctuation analysis (MFDFA) of the time series of return generated by our recently-proposed Ising financial market model with underlying small world topology. The result of the MFDFA shows that there exists obvious multifractal scaling behavior in produced time series. We compare the MFDFA results for original time series with those for shuffled series, and find that its multifractal nature is due to two factors: broadness of probability density function of the series and different correlations in small- and large-scale fluctuations. This may provide new insight to the problem of the origin of multifractality in financial time series. 展开更多
关键词 A Multifractal detrended Fluctuation analysis of the Ising Financial Markets Model with Small World Topology
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Cross-correlation analysis of crude oil and new energy markets: A new perspective based on carbon emission market 被引量:1
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作者 FENG You-shuai LING Mei-jun 《Ecological Economy》 2019年第1期2-18,共17页
Taking the return series of the EU carbon allowance price, WTI crude oil price, the European renewable energy index and Shenzhen carbon emission price, Daqing crude oil price, the China securities new energy index as ... Taking the return series of the EU carbon allowance price, WTI crude oil price, the European renewable energy index and Shenzhen carbon emission price, Daqing crude oil price, the China securities new energy index as sample data, the multifractal detrend cross-correlation analysis method(MF-DCCA)is used to research the dynamic cross-correlation relationships among the carbon emission market, crude oil market and the new energy market in Europe and China and the source of the multifractality. The empirical analysis shows that the cross-correlations among the carbon emission market, crude oil market and new energy market in Europe and China have all significant multifractal characteristics. Moreover, the multifractal strength of cross-correlation between the carbon emission market and crude oil market is less than that between the carbon emission market and new energy market in Europe. The Chinese market is the opposite. In addition, the multifractal strength of cross-correlation between the crude oil market and new energy market in Europe is more than that between the crude oil market and new energy market in China. It is also found that the long-range correlation of the sequences themselves and the fat-tailed distribution in fluctuations are the common causes of the multifractality, and the fat-tailed in fluctuations distribution contributes more to the multifractals of the series. 展开更多
关键词 carbon emission market crude oil market new energy market cross-correlation multifractal statistical analysis
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Effects of quantization on detrended fluctuation analysis
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作者 朱松盛 徐泽西 +1 位作者 殷奎喜 徐寅林 《Chinese Physics B》 SCIE EI CAS CSCD 2011年第5期153-158,共6页
Detrended fluctuation analysis (DFA) is a method foro estimating the long-range power-law correlation exponent in noisy signals. It has been used successfully in many different fields, especially in the research of ... Detrended fluctuation analysis (DFA) is a method foro estimating the long-range power-law correlation exponent in noisy signals. It has been used successfully in many different fields, especially in the research of physiological signals. As an inherent part of these studies, quantization of continuous signals is inevitable. In addition, coarse-graining, to transfer original signals into symbol series in symbolic dynamic analysis, can also be considered as a quantization-like operation. Therefore, it is worth considering whether the quantization of signal has any effect on the result of DFA and if so, how large the effect will be. In this paper we study how the quantized degrees for three types of noise series (anti-correlated, uncorrelated and long-range power-law correlated signals) affect the results of DFA and find that their effects are completely different. The conclusion has an essential value in choosing the resolution of data acquisition instrument and in the processing of coarse-graining of signals. 展开更多
关键词 detrended fluctuation analysis QUANTIZATION
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Crossover Phenomena in Detrended Fluctuation Analysis Used in Financial Markets
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作者 MA Shi-Hao 《Communications in Theoretical Physics》 SCIE CAS CSCD 2009年第2期358-362,共5页
A systematic analysis of Shanghai and Japan stock indices for the period of Jan. 1984 to Dec. 2005 is performed. After stationarity is verified by ADF (Augmented Dickey-Fuller) test, the power spectrum of the data e... A systematic analysis of Shanghai and Japan stock indices for the period of Jan. 1984 to Dec. 2005 is performed. After stationarity is verified by ADF (Augmented Dickey-Fuller) test, the power spectrum of the data exhibits a power law decay as a whole characterized by 1/f^β processes with possible long range correlations. Subsequently, by using the method of detrended fluctuation analysis (DFA) of the general volatility in the stock markets, we find that the long-range correlations are occurred among the return series and the crossover phenomena exhibit in the results obviously.Further, Shanghai stock market shows long-range correlations in short time scale and shows short-range correlations in long time scale. Whereas, for Japan stock market, the data behaves oppositely absolutely. Last, we compare the varying of scale exponent in large volatility between two stock markets. All results obtained may indicate the possibility of characteristic of multifractal scaling behavior of the financial markets. 展开更多
关键词 financial market crossover phenomena detrended fluctuation analysis
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Asymptotic Analysis of Estimated Cyclic Cross-Correlation Function Between Stationary and Cyclostationary Processes
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作者 黄知涛 王炜华 +1 位作者 周一宇 姜文利 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2003年第3期87-91,共5页
The cyclic cross-correlation between a stationary process and a cyclostationary process at cycle frequency α(≠ 0)is identically zero under an ideal condition, which indicates that a cyclic cross-correlation method p... The cyclic cross-correlation between a stationary process and a cyclostationary process at cycle frequency α(≠ 0)is identically zero under an ideal condition, which indicates that a cyclic cross-correlation method performs much better than the conventional cross-correlation method in suppressing the stationary noise or interference. But unfortunately, the cyclic cross-correlation will not really approach zero due to the limited data length in some real conditions. In this paper, the quantitative relation between the data length and the estimated cyclic cross-correlation is deduced, and some useful conclusions are drawn, which are proven by some computer simulations. The conclusion in this paper is really useful for the practical application of cyclostationary signal processing. 展开更多
关键词 CYCLOSTATIONARITY Cyclic cross-correlation Convergence analysis.
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A Sleep Scoring System Using EEG Combined Spectral and Detrended Fluctuation Analysis Features
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作者 Amr F. Farag Shereen M. El-Metwally Ahmed A. Morsy 《Journal of Biomedical Science and Engineering》 2014年第8期584-592,共9页
Most of sleep disorders are diagnosed based on the sleep scoring and assessments. The purpose of this study is to combine detrended fluctuation analysis features and spectral features of single electroencephalograph (... Most of sleep disorders are diagnosed based on the sleep scoring and assessments. The purpose of this study is to combine detrended fluctuation analysis features and spectral features of single electroencephalograph (EEG) channel for the purpose of building an automated sleep staging system based on the hybrid prediction engine model. The testing results of the model were promising as the classification accuracies were 98.85%, 92.26%, 94.4%, 95.16% and 93.68% for the wake, non-rapid eye movement S1, non-rapid eye movement S2, non-rapid eye movement S3 and rapid eye movement sleep stages, respectively. The overall classification accuracy was 85.18%. We concluded that it might be possible to employ this approach to build an industrial sleep assessment system that reduced the number of channels that affected the sleep quality and the effort excreted by sleep specialists through the process of the sleep scoring. 展开更多
关键词 Automated SLEEP STAGING detrended FLUCTUATION analysis (DFA) Decision Tree Multi-Layer PERCEPTRON (MLP)
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Detrended Fluctuation Analysis of Heart Rate and SaO_2 in Hypoxia
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作者 LIU Yuan-yuan YU Meng-sun 《Chinese Journal of Biomedical Engineering(English Edition)》 2011年第3期130-135,共6页
Detrended fluctuation analysis (DFA) is fit for studies on the long-range exponential correlation of non-stationary time serial. In this paper, in order to find a hy- poxia adaptability evaluation criterion, the hea... Detrended fluctuation analysis (DFA) is fit for studies on the long-range exponential correlation of non-stationary time serial. In this paper, in order to find a hy- poxia adaptability evaluation criterion, the heart rate and SaO2 signals are analyzed by this method. The demarcate exponent about fit-good-group and fit-bad-group in hy- poxia and normal air are calculated and compared. The result shows a is different in different situation, the α in hypoxia is much higher than α of breath in normal air. And α of fit-good-group is higher than fit-bad-group. It shows that DFA could be a good criterion to analyze hypoxia adaptability, which is useful in the analysis of hypoxia phys- iology signal. 展开更多
关键词 detrended fluctuation analysis heart rate SAO2 HYPOXIA
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The Effectiveness Evaluation of Two Kinds of Fractal Sequences on Detrended Fluctuation Analysis
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作者 Danying Xie Li Wan Yongqiang Zhu 《数学计算(中英文版)》 2014年第2期58-62,共5页
关键词 序列数据 波动分析 效能评估 HURST指数 分数布朗运动 分形 估计精度 高斯噪声
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A new protection scheme for PV-wind based DC-ring microgrid by using modified multifractal detrended fluctuation analysis
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作者 Kanche Anjaiah Pradipta Kishore Dash Mrutyunjaya Sahani 《Protection and Control of Modern Power Systems》 2022年第1期100-123,共24页
This paper presents fault detection,classification,and location for a PV-Wind-based DC ring microgrid in the MATLAB/SIMULINK platform.Initially,DC fault signals are collected from local measurements to examine the out... This paper presents fault detection,classification,and location for a PV-Wind-based DC ring microgrid in the MATLAB/SIMULINK platform.Initially,DC fault signals are collected from local measurements to examine the outcomes of the proposed system.Accurate detection is carried out for all faults,(i.e.,cable and arc faults)under two cases of fault resistance and distance variation,with the assistance of primary and secondary detection techniques,i.e.second-order differential current derivatived2I3 dt2and sliding mode window-based Pearson’s correlation coefficient.For fault classification a novel approach using modified multifractal detrended fluctuation analysis(M-MFDFA)is presented.The advantage of this method is its ability to estimate the local trends of any order polynomial function with the help of polynomial and trigonometric functions.It also doesn’t require any signal processing algorithm for decomposition resulting and this results in a reduction of computational burden.The detected fault signals are directly passed through the M-MFDFA classifier for fault type classification.To enhance the performance of the proposed classifier,statistical data is obtained from the M-MFDFA feature vectors,and the obtained data is plotted in 2-D and 3-D scatter plots for better visualization.Accurate fault distance estimation is carried out for all types of faults in the DC ring bus microgrid with the assistance of recursive least squares with a forgetting factor(FF-RLS).To verify the performance and superiority of the proposed classifier,it is compared with existing classifiers in terms of features,classification accuracy(CA),and relative computational time(RCT). 展开更多
关键词 DC ring microgrid Differential current Fault resistance Detection Classification Fault location estimation Multifractal detrended fluctuation analysis
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Wave height statistical characteristic analysis 被引量:4
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作者 LIU Guilin CHEN Baiyu +3 位作者 WANG Liping ZHANG Shuaifang ZHANG Kuangyuan LEI Xi 《Journal of Oceanology and Limnology》 SCIE CAS CSCD 2019年第2期448-460,共13页
When exploring the temporal and spatial change law of ocean environment, the most common method used is using smaller-scale observed data to derive the change law for a larger-scale system. For instance, using 30-year... When exploring the temporal and spatial change law of ocean environment, the most common method used is using smaller-scale observed data to derive the change law for a larger-scale system. For instance, using 30-year observation data to derive 100-year return period design wave height. Therefore, the study of inherent self-similarity in ocean hydrological elements becomes increasingly important to the study of multi-year return period design wave height derivation. In this paper, we introduced multifractal to analyze the statistical characteristics of wave height series data observed from oceanic hydrological station. An improvement is made to address the existing problems of the multifractal detrended fluctuation analysis (MF-DFA) method, where trend function showed a discontinuity between intervals. The improved MFDFA method is based on signal mode decomposition, replacing piecewise polynomial fitting used in the original method. We applied the proposed method to the wave height data collected at Chaolian Island, Shandong, China, from 1963 to 1989 and was able to conclude the wave height sequence presented weak multi-fractality. This result provided strong support to the past research on the derivation of multi-year return period design wave height with observed data. Moreover, the new method proposed in this paper also provides a new perspective to explore the intrinsic characteristic of data. 展开更多
关键词 wave HEIGHT PARTITION function MULTIFRACTAL spectrum MULTIFRACTAL detrended FLUCTUATION analysis (MF-DFA) signal mode DECOMPOSITION
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Correlation analysis between the Aral Sea shrinkage and the Amu Darya River 被引量:1
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作者 WANG Min CHEN Xi +6 位作者 CAO Liangzhong KURBAN Alishir SHI Haiyang WU Nannan EZIZ Anwar YUAN Xiuliang Philippe DE MAEYER 《Journal of Arid Land》 SCIE CSCD 2023年第7期757-778,共22页
The shrinkage of the Aral Sea,which is closely related to the Amu Darya River,strongly affects the sustainability of the local natural ecosystem,agricultural production,and human well-being.In this study,we used the B... The shrinkage of the Aral Sea,which is closely related to the Amu Darya River,strongly affects the sustainability of the local natural ecosystem,agricultural production,and human well-being.In this study,we used the Bayesian Estimator of Abrupt change,Seasonal change,and Trend(BEAST)model to detect the historical change points in the variation of the Aral Sea and the Amu Darya River and analyse the causes of the Aral Sea shrinkage during the 1950–2016 period.Further,we applied multifractal detrend cross-correlation analysis(MF-DCCA)and quantitative analysis to investigate the responses of the Aral Sea to the runoff in the Amu Darya River,which is the main source of recharge to the Aral Sea.Our results showed that two significant trend change points in the water volume change of the Aral Sea occurred,in 1961 and 1974.Before 1961,the water volume in the Aral Sea was stable,after which it began to shrink,with a shrinkage rate fluctuating around 15.21 km3/a.After 1974,the water volume of the Aral Sea decreased substantially at a rate of up to 48.97 km3/a,which was the highest value recorded in this study.In addition,although the response of the Aral Sea's water volume to its recharge runoff demonstrated a complex non-linear relationship,the replenishment of the Aral Sea by the runoff in the lower reaches of the Amu Darya River was identified as the dominant factor affecting the Aral Sea shrinkage.Based on the scenario analyses,we concluded that it is possible to slow down the retreat of the Aral Sea and restore its ecosystem by increasing the efficiency of agricultural water use,decreasing agricultural water use in the middle and lower reaches,reducing ineffective evaporation from reservoirs and wetlands,and increasing the water coming from the lower reaches of the Amu Darya River to the 1961–1973 level.These measures would maintain and stabilise the water area and water volume of the Aral Sea in a state of ecological restoration.Therefore,this study focuses on how human consumption of recharge runoff affects the Aral Sea and provides scientific perspective on its ecological conservation and sustainable development. 展开更多
关键词 Aral Sea shrinkage recharge runoff Amu Darya River Syr Darya River multifractal detrend cross-correlation analysis(MF-DCCA) Bayesian Estimator of Abrupt change Seasonal change and Trend(BEAST) Central Asia
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Multifractal Analysis of Human Heartbeat in Sleep 被引量:2
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作者 丁亮晶 彭虎 +1 位作者 蔡世民 周佩玲 《Chinese Physics Letters》 SCIE CAS CSCD 2007年第7期2149-2152,共4页
We study the dynamical properties of heart rate variability (HRV) in sleep by analysing the scaling behaviour with the multifractal detrended fluctuation analysis method. It is well known that heart rate is regulate... We study the dynamical properties of heart rate variability (HRV) in sleep by analysing the scaling behaviour with the multifractal detrended fluctuation analysis method. It is well known that heart rate is regulated by the interaction of two branches of the autonomic nervous system: the parasympathetic and sympathetic nervous systems. By investigating the multifractal properties of light, deep, rapid-eye-movement (REM) sleep and wake stages, we firstly find an increasing multifractal behaviour during REM sleep which may be caused by augmented sympathetic activities relative to non-REM sleep. In addition, the investigation of long-range correlations of HRV in sleep with second order detrended fluctuation analysis presents irregular phenomena. These findings may be helpful to understand the underlying regulating mechanism of heart rate by autonomic nervous system during wake-sleep transitions. 展开更多
关键词 detrended FLUCTUATION analysis RATE-VARIABILITY DYNAMICS WAVELETS BEHAVIOR SIGNALS REGIONS
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