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A method based on multifractal detrended fluctuation analysis(DFA)， which is adaptable for unsteady images， is introduced to segment retina images. In this method， histogram equalization is first used to precondition images for the enhancement of blood vessels， and then， the generalized Hurst index of images is calculated by multifractal DFA. The blood vessel index is used to segment the blood vessels. Finally， morphological postprocessing is used to get the final blood vessel images. Experiments based on DIARETDE0 and DIARETDE1 databases show that the proposed method has better integrity and connectivity in the treatment of retinal lesions， and it can extract the main body of blood vessels better， which has a good clinical value. [ABSTRACT FROM AUTHOR]

Ｉｎ ｏｒｄｅｒ ｔｏ ｉｎｖｅｓｔｉｇａｔｅ ｓｅｌｆ⁃ｓｉｍｉｌａｒｉｔｙ ａｎｄ ｌｏｎｇ⁃ｒａｎｇ ｄｅｐｅｎｄｅｎｃｅ ｏｆ ｗｉｎｄ ｓｐｅｅｄ ｔｉｍｅ ｓｅｒｉｅｓ， ｔｈｅ ｒｅｓｃａｌｅｄ ｒａｎｇｅ ａｎａｌｙｓｉｓ ａｎｄ ｔｈｅ ｄｅｔｒｅｎｄｅｄ ｆｌｕｃｔｕａｔｉｏｎ ａｎａｌｙｓｉｓ （ＤＦＡ） ｗｅｒｅ ｃａｒｒｉｅｄ ｏｕｔ ｔｏ ｃａｌｃｕｌａｔｅ ｔｈｅ Ｈｕｒｓｔ ｅｘｐｏｎｅｎｔ ｏｆ ｔｈｅ ｗｉｎｄ ｓｐｅｅｄ ｔｉｍｅ ｓｅｒｉｅｓ． Ｔｈｅ ｐｏｗｅｒ ｓｐｅｃｔｒａｌ ｄｅｎｓｉｔｙ ｗａｓ ａｎａｌｙｚｅｄ ａｎｄ ｔｈｅ ｓｐｅｃｔｒａｌ ｉｎｄｅｘｅｓ ｗｅｒｅ ｃａｌｃｕｌａｔｅｄ． Ｔｈｅ ｒｅｓｕｌｔｓ ｓｈｏｗ ｔｈａｔ， ｔｈｅ Ｈｕｒｓｔ ｅｘｐｏ⁃ ｎｅｎｔｓ ｃａｌｃｕｌａｔｅｄ ｗｉｔｈ ｔｈｅ ｂｏｔｈ ｍｅｔｈｏｄｓ ａｒｅ ｃｌｏｓｅ ｔｏ １， ｗｈｉｃｈ ｍｅａｎｓ ｔｈａｔ ｔｈｅ ｗｉｎｄ ｓｐｅｅｄ ｔｉｍｅ ｓｅｒｉｅｓ ｈａｓ ｓｔｒｏｎｇ ｓｅｌｆ⁃ｓｉｍｉｌａｒｉｔｙ ａｎｄ ｌｏｎｇ⁃ｒａｎｇｅ ｐｏｓｉｔｉｖｅ ｄｅｐｅｎｄｅｎｃｅ． Ｈｏｗｅｖｅｒ， ｔｈｅ Ｈｕｒｓｔ ｉｎｄｅ⁃ ｘｅｓ ｆｒｏｍ ｔｈｅ ２ ｍｅｔｈｏｄｓ ａｒｅ ｄｉｆｆｅｒｅｎｔ， ｗｈｉｃｈ ｍｅａｎｓ ｔｈａｔ ｔｈｅ ＤＦＡ ｍｅｔｈｏｄ ｃｏｕｌｄ ｒｅｆｌｅｃｔ ｔｈｅ ｐｏｗ⁃ ｅｒ⁃ｌａｗ ｆｅａｔｕｒｅ ｏｆ ｔｈｅ ｎｏｎ⁃ｓｔａｔｉｏｎａｒｙ ｗｉｎｄ ｓｐｅｅｄ ｔｉｍｅ ｓｅｒｉｅｓ． Ｆｕｒｔｈｅｒｍｏｒｅ， ｔｈｅ ｒｅｓｕｌｔｓ ｏｆ ｔｈｅ Ｈｕｒｓｔ ｅｘｐｏｎｅｎｔｓ ａｎｄ ｔｈｅ ｓｐｅｃｔｒａｌ ｉｎｄｅｘｅｓ ｓｈｏｗ ｔｈａｔ ｔｈｅ ｗｉｎｄ ｓｐｅｅｄ ｆｌｕｃｔｕａｔｉｏｎ ｂｅｌｏｎｇｓ ｔｏ ｔｈｅ “１／ ｆ ｆｌｕｃｔｕａｔｉｏｎ”． Ｔｈｅ ｃｏｎｃｌｕｓｉｏｎｓ ｏｆｆｅｒ ｓｏｍｅ ｒｅｆｅｒｅｎｃｅｓ ｆｏｒ ｆｕｒｔｈｅｒ ｓｔｕｄｙ ｏｎ ｆｒａｃｔａｌ ｃｈａｏｓ ａｎｄ ｓｈｏｒｔ⁃ｔｉｍｅ ｗｉｎｄ ｓｐｅｅｄ ｐｒｅｄｉｃｔｉｏｎ． [ABSTRACT FROM AUTHOR]

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The nonlinearity and non-stationarity are two kinds of characteristics of gear fault vibration signals. The detrended fluctuation analysis (DFA) is introduced to extract the characteristics of vibration signals. With this method, the gear vibration signals acquired from experimental bench are analyzed. The logarithm scale-fluctuation function maps of DFA show that the signals are double-scaling which mean that there are different power-law correlated between scale and fluctuation amplitude in different time scale. The reason of double-scaling was discussed and a feature vector of gear vibration signal which consisted of the small scale exponent and the intercept was suggested. With proposed feature vector, 100 groups of training signals corresponding to different fault conditions are described by Gaussian mixture model and 50 groups of test signals are classified by maximum Bayes classification. The results verify that higher failure recognition rate can be got by proposed feature extraction method. [ABSTRACT FROM AUTHOR]

Using the ten day sunshine duration data of 107 meteorological stations in Henan Province from 1961 to 2012, spatial temporal variation characteristics of ten day sunshine duration were analyzed, and the scale invariance analysis of ten day sunshine duration was studied by using the method of detrended fluctuation analysis. The results showed that the means of ten day sunshine duration and its standardized error among stations were 57.90 and 9.18 h, respectively, and their probability distributions were not subject to normal distribution. The cumulative abnormal of sun shine duration had a distinct linear increasing trend, however, its square deviation among the stations was of phase characteristics. The scale index of ten-day sunshine of each station was above 0.5, indicated that time series of scale index was of permanence. Variation of scale index among stations was small, which obeyed the normal distribution. [ABSTRACT FROM AUTHOR]