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Andrei Velichko, Maksim Belyaev, Yuriy Izotov, Murugappan Murugappan and Hanif Heidari
Entropy measures are effective features for time series classification problems. Traditional entropy measures, such as Shannon entropy, use probability distribution function. However, for the effective separation of time series, new entropy estimation me...
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Luciano Telesca, Anh Tuan Thai, Michele Lovallo, Dinh Trong Cao and Le Minh Nguyen
The reservoir-triggered seismicity at the Song Tranh 2 reservoir in Vietnam is investigated by using Shannon entropy, a well-known informational method used to analyze complexity in time series in terms of disorder and uncertainty. The application of the...
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João Sequeira, Jorge Louçã, António M. Mendes and Pedro G. Lind
We analyze the empirical series of malaria incidence, using the concepts of autocorrelation, Hurst exponent and Shannon entropy with the aim of uncovering hidden variables in those series. From the simulations of an agent model for malaria spreading, we ...
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Xingming Zeng, Haiyuan Liu and Hao He
Prediction of intrinsic disordered proteins is a hot area in the field of bio-information. Due to the high cost of evaluating the disordered regions of protein sequences using experimental methods, we used a low-complexity prediction scheme. Sequence com...
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Robert Graczyk and Igal Sason
Stationary memoryless sources produce two correlated random sequences ????
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n
and ????
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n
. A guesser seeks to recover ????
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in two stages, by first guessing ????
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n
and then ????
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. The contributions of this work are twofold: (1) We characte...
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