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Moderate deviations for I.I.D. random variables

Peter EichelsbacherMatthias Löwe — 2003

ESAIM: Probability and Statistics

We derive necessary and sufficient conditions for a sum of i.i.d. random variables i = 1 n X i / b n – where b n n 0 , but b n n – to satisfy a moderate deviations principle. Moreover we show that this equivalence is a typical moderate deviations phenomenon. It is not true in a large deviations regime.

Capacity bounds for the CDMA system and a neural network: a moderate deviations approach

Matthias LöweFranck Vermet — 2009

ESAIM: Probability and Statistics

We study two systems that are based on sums of weakly dependent Bernoulli random variables that take values 1 with equal probabilities. We show that already one step of the so-called soft decision parallel interference cancellation, used in the third generation of mobile telecommunication CDMA, is able to considerably increase the number of users such a system can host. We also consider a variant of the well-known Hopfield model of neural networks. We show that this variant proposed by Amari and...

Moderate Deviations for I.I.D. Random Variables

Peter EichelsbacherMatthias Löwe — 2010

ESAIM: Probability and Statistics

We derive necessary and sufficient conditions for a sum of i.i.d. random variables i = 1 n X i / b n – where b n n 0 , but b n n – to satisfy a moderate deviations principle. Moreover we show that this equivalence is a typical moderate deviations phenomenon. It is not true in a large deviations regime.

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