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Uniform Random Number Generators
Journal of the ACM, 1965Abstract : This paper discusses the testing of methods for generating uniform numbers in a computer--the commonly used multiplicative and mixed congruential generators as well as two methods. Tests proposed here are more stringent than those usually applied, because the usual tests for randomness have passed several of the commonly used pprocedures ...
M. Donald MacLaren, George Marsaglia
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Quantum random number generator vs. random number generator
2016 International Conference on Communications (COMM), 2016A random number generator produces a periodic sequence of numbers on a computer. The starting point can be random, but after it is chosen, everything else is deterministic. A random number generator produces a periodic sequence of numbers on a computer. The starting point can be random, but after it is chosen, everything else is deterministic.
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Pseudo Random Number Generators
2013In a first step the definition of randomness and the mathematical definition of random numbers and sequences are addressed. We move on to describe the properties of an ideal random number generator and concentrate then on pseudo random number generators which are the basic tool in the application of stochastic methods in Computational Physics ...
Benjamin A. Stickler, Ewald Schachinger
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Random number generators for microcomputers
Computer Programs in Biomedicine, 1983The feasibility of random number generation using microcomputers is discussed and the appropriateness of alternative algorithms is evaluated on the basis of several criteria of statistical randomness. The relative deficiencies of each algorithm are cited and a modified Fibonacci generator is recommended for use in the microcomputer environment.
W, Rosenbaum, J, Syrotuik, R, Gordon
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Random Numbers Generation and Testing
200530.1 Definition of a random sequence 715 30.2 Random number generators 717 History • Properties of random number generators • Types of random number generators • Popular random number generators 30.3 Testing of random number generators 722 30.4 Testing a device 722 30.5 Statistical (empirical) tests 723 30.6 Some examples of statistical models on Σ 725
Lange, T., Lubicz, D., Weigl, A.
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A Natural Random Number Generator
International Statistical Review / Revue Internationale de Statistique, 1996Summary: Since the introduction of the ``middle square'' method by John von Neumann for the production of ``pseudo-random'' numbers in about 1949, hundreds of other methods have been introduced. While each may have some virtue a single uniformly superior method has not emerged.
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