Estimation of Shannon and Rényi entropies of unknown discrete distributions is a fundamental problem in statistical property testing and an active research topic in both theoretical computer science and information theory. Tight bounds on the number of samples to estimate these entropies have been established in the classical setting, while little is known about their quantum counterparts. In t...

We presents a refined multiscale Shannon entropy for analyzing electroencephalogram (EEG), which reflects the underlying dynamics of EEG over multiple scales. The rationale behind this method is that neurological signals such as EEG possess distinct dynamics over different spectral modes. To deal with the nonlinear and nonstationary nature of EEG, the recently developed empirical mode decomposi...

Data mining is an interdisciplinary field of computer science and is referred to extracting or mining knowledge from large amounts of data. Classification is one of the data mining techniques that maps the data into the predefined classes and groups. It is used to predict group membership for data instances. There are many areas that adapt Data mining techniques such as medical, marketing, tele...

The physical concept of entropy as it is used in thermodynamics is related to the mathematical formulation of a Shannon entropy. Usually only the Shannon entropy of equilibrium distributions such as a canonical distribution is considered. Large deviations statistics goes beyond that framework. Entropies are considered for arbitrary distributions or physical states, and they describe, e.g., \how...

We apply Shannon entropy as a measure of information content in survey data, and define information efficiency as the empirical entropy divided by the maximum attainable entropy. In a case study of the Norwegian Function Assessment Scale, entropy calculations show that the 5-point response version has higher information efficiency than the 4-point version.

The global maximum of an entropy function with different decision levels for a three-level scalar quantizer performed after a discrete wavelet transform was derived. Herein, we considered the case of entropy-constrained scalar quantization capable of avoiding many compression ratio reductions as the mean squared error was minimized. We also dealt with the problem of minimum entropy with an erro...

today, along with enhancement of social well-being andeconomic development, demand for transportation is growing increasingly.many countries are seeking for providing transportation servicesat a reasonable price. therefore, optimization of carrying goods on nationalor international roads is highly important in terms of costs andtransportation indicator, so that the goods are shipped at minimumc...