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LevelSpacing Distributions and the Airy Kernel
 COMMUNICATIONS IN MATHEMATICAL PHYSICS
, 1994
"... Scaling levelspacing distribution functions in the "bulk of the spectrum" in random matrix models of N x N hermitian matrices and then going to the limit N — » oo leads to the Fredholm determinant of the sine kernel sinπ(x — y)/π(x — y). Similarly a scaling limit at the "edge o ..."
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Cited by 430 (24 self)
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Scaling levelspacing distribution functions in the "bulk of the spectrum" in random matrix models of N x N hermitian matrices and then going to the limit N — » oo leads to the Fredholm determinant of the sine kernel sinπ(x — y)/π(x — y). Similarly a scaling limit at the &
LevelSpacing Distributions and the Airy Kernel
, 1992
"... Scaling levelspacing distribution functions in the “bulk of the spectrum ” in random matrix models of N × N hermitian matrices and then going to the limit N → ∞, leads to the Fredholm determinant of the sine kernel sinπ(x − y)/π(x − y). Similarly a scaling limit at the “edge of the spectrum ” leads ..."
Abstract
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Scaling levelspacing distribution functions in the “bulk of the spectrum ” in random matrix models of N × N hermitian matrices and then going to the limit N → ∞, leads to the Fredholm determinant of the sine kernel sinπ(x − y)/π(x − y). Similarly a scaling limit at the “edge of the spectrum
ITD 92/93–11 LevelSpacing Distributions and the Airy Kernel
, 1992
"... Scaling levelspacing distribution functions in the “bulk of the spectrum ” in random matrix models of N ×N hermitian matrices and then going to the limit N → ∞, leads to the Fredholm determinant of the sine kernel sin π(x − y)/π(x − y). Similarly a double scaling limit at the “edge of the spectrum ..."
Abstract
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Scaling levelspacing distribution functions in the “bulk of the spectrum ” in random matrix models of N ×N hermitian matrices and then going to the limit N → ∞, leads to the Fredholm determinant of the sine kernel sin π(x − y)/π(x − y). Similarly a double scaling limit at the “edge of the spectrum
Extension of levelspacing universality
 Phys. Rev. E
, 1997
"... In the theory of random matrices, several properties are known to be universal, i.e. independent of the specific probability distribution. For instance Dyson’s shortdistance universality of the correlation functions implies the universality of P(s), the levelspacing distribution. We first briefly ..."
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Cited by 19 (2 self)
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In the theory of random matrices, several properties are known to be universal, i.e. independent of the specific probability distribution. For instance Dyson’s shortdistance universality of the correlation functions implies the universality of P(s), the levelspacing distribution. We first briefly
Distributed Database Systems
"... this article, we discuss the fundamentals of distributed DBMS technology. We address the data distribution and architectural design issues as well as the algorithms that need to be implemented to provide the basic DBMS functions such as query processing, concurrency control, reliability, and replica ..."
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Cited by 588 (26 self)
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this article, we discuss the fundamentals of distributed DBMS technology. We address the data distribution and architectural design issues as well as the algorithms that need to be implemented to provide the basic DBMS functions such as query processing, concurrency control, reliability
Performance Analysis of the IEEE 802.11 Distributed Coordination Function
, 2000
"... Recently, the IEEE has standardized the 802.11 protocol for Wireless Local Area Networks. The primary medium access control (MAC) technique of 802.11 is called distributed coordination function (DCF). DCF is a carrier sense multiple access with collision avoidance (CSMA/CA) scheme with binary slott ..."
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Cited by 1869 (1 self)
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Recently, the IEEE has standardized the 802.11 protocol for Wireless Local Area Networks. The primary medium access control (MAC) technique of 802.11 is called distributed coordination function (DCF). DCF is a carrier sense multiple access with collision avoidance (CSMA/CA) scheme with binary
Entity Authentication and Key Distribution
, 1993
"... Entity authentication and key distribution are central cryptographic problems in distributed computing  but up until now, they have lacked even a meaningful definition. One consequence is that incorrect and inefficient protocols have proliferated. This paper provides the first treatment of these p ..."
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Cited by 578 (13 self)
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Entity authentication and key distribution are central cryptographic problems in distributed computing  but up until now, they have lacked even a meaningful definition. One consequence is that incorrect and inefficient protocols have proliferated. This paper provides the first treatment
The structure and function of complex networks
 SIAM REVIEW
, 2003
"... Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, ..."
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Cited by 2600 (7 self)
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, including such concepts as the smallworld effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images.
 IEEE Trans. Pattern Anal. Mach. Intell.
, 1984
"... AbstractWe make an analogy between images and statistical mechanics systems. Pixel gray levels and the presence and orientation of edges are viewed as states of atoms or molecules in a latticelike physical system. The assignment of an energy function in the physical system determines its Gibbs di ..."
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Cited by 5126 (1 self)
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AbstractWe make an analogy between images and statistical mechanics systems. Pixel gray levels and the presence and orientation of edges are viewed as states of atoms or molecules in a latticelike physical system. The assignment of an energy function in the physical system determines its Gibbs
Estimating the Support of a HighDimensional Distribution
, 1999
"... Suppose you are given some dataset drawn from an underlying probability distribution P and you want to estimate a "simple" subset S of input space such that the probability that a test point drawn from P lies outside of S is bounded by some a priori specified between 0 and 1. We propo ..."
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Cited by 783 (29 self)
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Suppose you are given some dataset drawn from an underlying probability distribution P and you want to estimate a "simple" subset S of input space such that the probability that a test point drawn from P lies outside of S is bounded by some a priori specified between 0 and 1. We
Results 1  10
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