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
Apoptosis proteins play an important role in the development and homeostasis of an organism. The elucidation of the subcellular locations and functions of these proteins is helpful for understanding the mechanism of p...Apoptosis proteins play an important role in the development and homeostasis of an organism. The elucidation of the subcellular locations and functions of these proteins is helpful for understanding the mechanism of programmed cell death. In this paper, the recurrent quantification analysis, Hilbert-Huang transform methods, the maximum relevance and minimum redundancy method and support vector machine are used to predict the subcellular location of apoptosis proteins. The validation of the jackknife test suggests that the proposed method can improve the prediction accuracy of the subcellular location of apoptosis proteins and its application may be promising in other fields.展开更多
基金Project supported by the National Natural Science Foundation of China (Grant No.11071282)the Chinese Program for New Century Excellent Talents in University (Grant No.NCET-08-06867)
文摘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.
基金supported by the National Natural Science Foundation of China (Grant No. 11071282)the Chinese Program for New Century Excellent Talents in University (Grant No. NCET-08-06867)+4 种基金the Natural Science Foundation of Hunan Province of China(Grant No. 10JJ7001)the Lotus Scholars Program of Hunan Province of Chinathe Aid Program for Science and Technology Innovative Research Team in Higher Educational Institutions of Hunan Province of Chinathe Australian Research Council (GrantNo. DP0559807)the Postgraduate Research and Innovation Project of Hunan Province of China (Grant No. CX2010B243)
文摘Apoptosis proteins play an important role in the development and homeostasis of an organism. The elucidation of the subcellular locations and functions of these proteins is helpful for understanding the mechanism of programmed cell death. In this paper, the recurrent quantification analysis, Hilbert-Huang transform methods, the maximum relevance and minimum redundancy method and support vector machine are used to predict the subcellular location of apoptosis proteins. The validation of the jackknife test suggests that the proposed method can improve the prediction accuracy of the subcellular location of apoptosis proteins and its application may be promising in other fields.