Multifractal detrended moving average analysis for texture representation

2014 ◽  
Vol 24 (3) ◽  
pp. 033127 ◽  
Author(s):  
Fang Wang ◽  
Lin Wang ◽  
Rui-Biao Zou
2014 ◽  
Vol 24 (2) ◽  
pp. 022101 ◽  
Author(s):  
Piotr Kowalczyk ◽  
Salam Nema ◽  
Paul Glendinning ◽  
Ian Loram ◽  
Martin Brown

2002 ◽  
Vol 92 (2) ◽  
pp. 541-549 ◽  
Author(s):  
Bruce D. Nearing ◽  
Richard L. Verrier

T-wave alternans is a marker of cardiac electrical instability with the potential for arrhythmia risk stratification. The modified moving average method was developed to measure alternans in settings with artifacts, noise, and nonstationary data. Algorithms were developed and performance characteristics were validated with simulated electrocardiograms (ECGs). Experimental laboratory ECGs with dynamically changing alternans values were analyzed. Alternans values estimated by modified moving average analysis correlated strongly with input alternans values ( r 2 = 0.9999). Rapidly changing alternans levels and phase reversals did not perturb the measurement. When heart rate was increased from 60 to 180 beats/min, with T-wave alternans apex moving from 237 to 103 ms after the R wave, the measured alternans peak varied <5% from input value. Simulated 50- to 1,000-μV motion artifact spikes typical of treadmill ECGs produced inaccuracies <2%. Alternans values in experimental laboratory study using standard electrodes tracked vulnerability to myocardial ischemia-induced ventricular fibrillation with 100% sensitivity and specificity at a cut point of 0.75 mV. Modified moving average analysis is a robust method that precisely measures T-wave alternans in settings with artifacts, noise, and nonstationary data typical of clinical ECGs and yields an accurate estimate of risk for ventricular fibrillation.


Fractals ◽  
2015 ◽  
Vol 23 (03) ◽  
pp. 1550034 ◽  
Author(s):  
YING-HUI SHAO ◽  
GAO-FENG GU ◽  
ZHI-QIANG JIANG ◽  
WEI-XING ZHOU

The detrending moving average (DMA) algorithm is one of the best performing methods to quantify the long-term correlations in nonstationary time series. As many long-term correlated time series in real systems contain various trends, we investigate the effects of polynomial trends on the scaling behaviors and the performances of three widely used DMA methods including backward algorithm (BDMA), centered algorithm (CDMA) and forward algorithm (FDMA). We derive a general framework for polynomial trends and obtain analytical results for constant shifts and linear trends. We find that the behavior of the CDMA method is not influenced by constant shifts. In contrast, linear trends cause a crossover in the CDMA fluctuation functions. We also find that constant shifts and linear trends cause crossovers in the fluctuation functions obtained from the BDMA and FDMA methods. When a crossover exists, the scaling behavior at small scales comes from the intrinsic time series while that at large scales is dominated by the constant shifts or linear trends. We also derive analytically the expressions of crossover scales and show that the crossover scale depends on the strength of the polynomial trends, the Hurst index, and in some cases (linear trends for BDMA and FDMA) the length of the time series. In all cases, the BDMA and the FDMA behave almost the same under the influence of constant shifts or linear trends. Extensive numerical experiments confirm excellently the analytical derivations. We conclude that the CDMA method outperforms the BDMA and FDMA methods in the presence of polynomial trends.


Author(s):  
Bohdan Kolomiiets ◽  
Ivan Seleznov ◽  
Ken Kiyono ◽  
Anton Popov ◽  
Elena Kolosova

Author(s):  
A.K. Madan ◽  
Rohit Dutt

In the present study, the application of a wide variety of topological descriptors was investigated for predicting hydrophobicity (clogP) of isatin analogues. A total of four topochemical indices selected through decision tree (DT) were used for the development of single index based models using moving average analysis (MAA). The overall accuracy of prediction varied from a minimum of 95% to a maximum of 98% with regard to hydrophobicity.The values of sensitivity, specificity and Mathew's correlation coefficient for all MAA based models with regard to hydrophobicity (clogP) was found to be =78%, =94% and =0.85 respectively, suggesting robustness of proposed models. Since the compounds with high clogP values were found effective in carboxylesterases (CEs) inhibition, therefore, highly hydrophobic ranges of proposed MAA models can easily be exploited for the design and development of potent CEs inhibitors.


Author(s):  
Nicholas Taylor ◽  
Kerri Coomber ◽  
Richelle Mayshak ◽  
Renee Zahnow ◽  
Jason Ferris ◽  
...  

Aims: This study aimed to explore the relationship between a 00:00 liquor restriction, introduced on 1 July 2016, and alcohol-related harm by examining its impact on serious assault numbers during high-alcohol hours (20:00–6:00 Friday and Saturday night), from 1 January 2009 to 30 June 2018. Methods: Two types of locations only impacted by the liquor restriction were identified: designated safe night precincts (SNPs) and other local government areas (LGAs). A times series autoregressive integrated moving average analysis was used to estimate the influence of liquor restrictions on police-recorded serious assaults in the two years following the policy introduction, for SNPs and LGAs separately. Results: Contrarily to our predictions, monthly police-recorded serious assaults did not significantly change within SNPs or LGAs following the introduction of liquor restrictions. Conclusion: The implementation of the Queensland liquor restriction did not result in a clear, unique reduction in serious assault trends. Further investigation should consider the impact of liquor restrictions in conjunction with other policy changes as public perception of restrictions and their cumulative impact may produce varied outcomes.


Fractals ◽  
2017 ◽  
Vol 25 (05) ◽  
pp. 1750041 ◽  
Author(s):  
PENG YUE ◽  
HAI-CHUAN XU ◽  
WEI CHEN ◽  
XIONG XIONG ◽  
WEI-XING ZHOU

The diagonal effect of orders is well documented in different markets, which states that the orders are more likely to be followed by the orders of the same aggressiveness and implies the presence of short-term correlations in order flows. Based on the order flow data of 43 Chinese stocks, we investigate if there are long-range correlations in the time series of order aggressiveness. The detrending moving average analysis shows that there are crossovers in the scaling behaviors of overall fluctuations and order aggressiveness exhibits linear long-term correlations. We design an objective procedure to determine the two Hurst indexes delimited by the crossover scale. We find no correlations in the short term and strong correlations in the long term for all stocks except for an outlier stock. The long-term correlation is found to depend on several firm specific characteristics. We also find that there are nonlinear long-term correlations in the order aggressiveness when we perform the multifractal detrending moving average analysis.


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