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

Matthias Löwe; Franck Vermet

ESAIM: Probability and Statistics (2009)

  • Volume: 13, page 343-362
  • ISSN: 1292-8100

Abstract

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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 Yanai [CITE] has a larger storage capacity than the original model. Both situations lead to the question of the moderate deviations behavior of a sum of weakly dependent Bernoulli random variables. We prove a moderate deviations principle for such a sum on the appropriate scale.

How to cite

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Löwe, Matthias, and Vermet, Franck. "Capacity bounds for the CDMA system and a neural network: a moderate deviations approach." ESAIM: Probability and Statistics 13 (2009): 343-362. <http://eudml.org/doc/250671>.

@article{Löwe2009,
abstract = { 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 Yanai [CITE] has a larger storage capacity than the original model. Both situations lead to the question of the moderate deviations behavior of a sum of weakly dependent Bernoulli random variables. We prove a moderate deviations principle for such a sum on the appropriate scale. },
author = {Löwe, Matthias, Vermet, Franck},
journal = {ESAIM: Probability and Statistics},
keywords = {Moderate deviations; large deviations; neural networks; storage capacity; Hopfield model; code division multiple access (CDMA) systems; parallel interference cancellation; moderate deviations; Hopfield network; code division multiple access- CDMA- systems; parallel interface cancellation},
language = {eng},
month = {7},
pages = {343-362},
publisher = {EDP Sciences},
title = {Capacity bounds for the CDMA system and a neural network: a moderate deviations approach},
url = {http://eudml.org/doc/250671},
volume = {13},
year = {2009},
}

TY - JOUR
AU - Löwe, Matthias
AU - Vermet, Franck
TI - Capacity bounds for the CDMA system and a neural network: a moderate deviations approach
JO - ESAIM: Probability and Statistics
DA - 2009/7//
PB - EDP Sciences
VL - 13
SP - 343
EP - 362
AB - 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 Yanai [CITE] has a larger storage capacity than the original model. Both situations lead to the question of the moderate deviations behavior of a sum of weakly dependent Bernoulli random variables. We prove a moderate deviations principle for such a sum on the appropriate scale.
LA - eng
KW - Moderate deviations; large deviations; neural networks; storage capacity; Hopfield model; code division multiple access (CDMA) systems; parallel interference cancellation; moderate deviations; Hopfield network; code division multiple access- CDMA- systems; parallel interface cancellation
UR - http://eudml.org/doc/250671
ER -

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