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4,851,492
Random Number Generation . . .
, 2005
"... We study random number generation using a biased source motivated by previous works ..."
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We study random number generation using a biased source motivated by previous works
ON THE RELIABILITY OF RANDOM NUMBER GENERATORS
"... of randomness, Autocorrelation function. In this paper we discuss major problems related to reliability of random number generators used for simulation studies. We propose the decimals of π as the most reliable random number generator as compared to certain real normal numbers as well as all familie ..."
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Cited by 2 (0 self)
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of randomness, Autocorrelation function. In this paper we discuss major problems related to reliability of random number generators used for simulation studies. We propose the decimals of π as the most reliable random number generator as compared to certain real normal numbers as well as all
Random Number Generation in gretl
"... The increasing popularity and complexity of random number intensive methods such as simulation and bootstrapping in econometrics requires researchers to have a good grasp of random number generation in general, and the specific generators that they employ in particular. Here, we discuss the random n ..."
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The increasing popularity and complexity of random number intensive methods such as simulation and bootstrapping in econometrics requires researchers to have a good grasp of random number generation in general, and the specific generators that they employ in particular. Here, we discuss the random
RANDOM NUMBER GENERATORS ARE CHAOTIC
"... We observe that pseudo-random number generators, familiar to all programmers, are derived from deterministic chaotic dynamical systems. We discuss the implications of this finding and compare computer generation of pseudo-random numbers to the theoretical ideal of a (noncomputable) random sequence. ..."
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Cited by 2 (1 self)
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We observe that pseudo-random number generators, familiar to all programmers, are derived from deterministic chaotic dynamical systems. We discuss the implications of this finding and compare computer generation of pseudo-random numbers to the theoretical ideal of a (noncomputable) random sequence
Gaussian random number generators
- ACM Computing Surveys
, 2007
"... Rapid generation of high quality Gaussian random numbers is a key capability for simulations across a wide range of disciplines. Advances in computing have brought the power to conduct simulations with very large numbers of random numbers and with it, the challenge of meeting increasingly stringent ..."
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Cited by 24 (2 self)
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Rapid generation of high quality Gaussian random numbers is a key capability for simulations across a wide range of disciplines. Advances in computing have brought the power to conduct simulations with very large numbers of random numbers and with it, the challenge of meeting increasingly stringent
RANDOM NUMBER GENERATOR
, 2012
"... Information in the form of online multimedia, bank accounts, or password usage for diverse applications needs some form of security. The core feature of many security systems is the generation of true random or pseudorandom numbers. Hence reliable generators of such numbers are indispensable. The fu ..."
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Information in the form of online multimedia, bank accounts, or password usage for diverse applications needs some form of security. The core feature of many security systems is the generation of true random or pseudorandom numbers. Hence reliable generators of such numbers are indispensable
The Bias of Random-Number Generators
"... To simulate chance occurrences, a computer can't literally toss a coin or roll a die. Instead, it relies on special numerical recipes for generating strings of shuffled digits that pass for random numbers. Such sequences of pseudorandom numbers play crucial roles not only in computer games but ..."
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To simulate chance occurrences, a computer can't literally toss a coin or roll a die. Instead, it relies on special numerical recipes for generating strings of shuffled digits that pass for random numbers. Such sequences of pseudorandom numbers play crucial roles not only in computer games
Pseudo-Random Number Generation on the
- in Cryptographic Hardware and Embedded Systems - CHES
, 1999
"... In this paper we explore pseudo-random number generation on the IBM 4758 Secure Crypto Coprocessor. In particular we compare several variants of Gennaro's provably secure generator, proposed at Crypto 2000, with more standard techniques based on the SHA-1 compression function. Our results s ..."
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Cited by 1 (0 self)
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In this paper we explore pseudo-random number generation on the IBM 4758 Secure Crypto Coprocessor. In particular we compare several variants of Gennaro's provably secure generator, proposed at Crypto 2000, with more standard techniques based on the SHA-1 compression function. Our results
Random Number Generator Recommendation by
"... The generation of uniform pseudo-random numbers between 0 and 1 is important in many numerical simulations. The purpose of this report is to explore the best generator(s) of such random numbers in terms of statistical properties and speed. While attempting to find the best generator in general, the ..."
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Cited by 1 (0 self)
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The generation of uniform pseudo-random numbers between 0 and 1 is important in many numerical simulations. The purpose of this report is to explore the best generator(s) of such random numbers in terms of statistical properties and speed. While attempting to find the best generator in general
Results 1 - 10
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4,851,492
