Develops EVD-based approximations for the FAS channel under full correlation to obtain closed-form OP and EC expressions.
Extreme value statistics of correlated random variables
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abstract
Extreme value statistics (EVS) concerns the study of the statistics of the maximum or the minimum of a set of random variables. This is an important problem for any time-series and has applications in climate, finance, sports, all the way to physics of disordered systems where one is interested in the statistics of the ground state energy. While the EVS of uncorrelated variables are well understood, little is known for strongly correlated random variables. Only recently this subject has gained much importance both in statistical physics and in probability theory. In this note, we will first review the classical EVS for uncorrelated variables and discuss few examples of correlated variables where analytical progress can be made.
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Exact mappings connect trapped fermions to random matrix theory, yielding edge statistics for fermions and Ginibre eigenvalues plus gap statistics for discrete random walks.
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Performance Analysis of Single-Antenna Fluid Antenna Systems via Extreme Value Theory
Develops EVD-based approximations for the FAS channel under full correlation to obtain closed-form OP and EC expressions.
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PhD thesis "Extreme value statistics of strongly correlated systems: fermions, random matrices and random walks"
Exact mappings connect trapped fermions to random matrix theory, yielding edge statistics for fermions and Ginibre eigenvalues plus gap statistics for discrete random walks.