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where 0 < b < 1 The Hurst parameter is related to b via b H 1 : 2 Hence, for long-range dependent time series, 1 < H < 1 As H 3 1, the degree of 2 long-range dependence increases A test for long-range dependence in a time series can be reduced to the question of determining whether H is sign cantly different from 1 2 In this chapter, we use two methods for testing self-similarity2 These methods are described more fully in Beran [5] and Taqqu et al [23], and are the same methods used in Leland et al [12] The rst method, the variance time plot, is based on the slowly decaying variance of a self-similar time series.



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This comparison of optical character recognition software includes: OCR engines , that do the actual character identification; Layout analysis software, that divide ...

The second method, the R=S plot, uses the fact that for a self-similar data set, the rescaled range or R=S statistic grows according to a power law with exponent H as a function of the number of points included Thus the plot of R=S against this number on a log log scale has a slope that is an estimate of H Figure 143 shows H-estimates based on variance time and R=S methods for three different network con gurations Each plot shows H as a function of the Pareto distribution parameter for a 1:05, 115, 125, 135, 165, and 195 Figure 143(a) shows the results for the baseline TCP Reno case in which network bandwidth and buffer capacity are both limited (15 Mb=s and 6 kB), resulting in an 4% packet drop rate for the most bursty case a 1:05 .





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FreeOCR is a free Optical Character Recognition Software for Windows and supports scanning from most Twain scanners and can also open most scanned PDF's and multi page Tiff images as well as popular image file formats. FreeOCR outputs plain text and can export directly to ...

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The plot shows that the Hurst parameter estimates vary with le size distribution in a roughly linear manner The H 3 a =2 line shows the values of H that would be predicted by the on=off model in an idealized case corresponding to a fractional Gaussian noise process Although their overall trends are similar (nearly coinciding at a 1:65), the slope of the simulated system with resource limitations and reliable transport layer running TCP Reno's congestion control is consistently less than 1, with an offset below the.

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2 A third method based on the periodgram was also used. However, this method is believed to be sensitive to low-frequency components in the series, which led in our case to a wide spread in the estimates; it is omittted here.

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Fig. 14.3 Hurst parameter estimates (TCP run): R=S and variance time for a 1:05, 1.35, 1.65 and 1.95. (a) Base run, (b) large bandwidth=large buffer, and (c) large buffer.

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