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A Survey on Error Exponents in Distributed Hypothesis Testing: Connections with Information Theory, Interpretations, and Applications

Author(s): Espinosa S; Silva JF; Céspedes S;

A central challenge in hypothesis testing (HT) lies in determining the optimal balance between Type I (false positive) and Type II (non-detection or false negative) error probabilities. Analyzing these errors' exponential rate of convergence, known as e ...

Article GUID: 39056958


Inter-protein residue covariation information unravels physically interacting protein dimers

Author(s): Salmanian S; Pezeshk H; Sadeghi M;

Background: Predicting physical interaction between proteins is one of the greatest challenges in computational biology. There are considerable various protein interactions and a huge number of protein sequences and synthetic peptides with unknown interacti ...

Article GUID: 33334319


Renyi entropy and mutual information measurement of market expectations and investor fear during the COVID-19 pandemic

Author(s): Lahmiri S; Bekiros S;

The COVID-19 pandemic has seriously affected world economies. In this regard, it is expected that information level and sharing between equity, digital currency, and energy markets has been altered due to the pandemic outbreak. Specifically, the resulting t ...

Article GUID: 32834621


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