The high-speed random number generator with the specified two-dimensional probability distribution O. V. Chernoyarov, V. P. Litvinenko, B. V. Matveev [et al.]
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ArticleContent type: Текст Media type: электронный Subject(s): генераторы случайных чисел | марковские модели | матрица переходных вероятностей | плотность вероятности | статистическое моделирование | гистограммыGenre/Form: статьи в сборниках Online resources: Click here to access online
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32nd European modeling and simulation symposium (EMSS 2020) : held at the 17th International multidisciplinary modeling and simulation multiconference (I3M 2020), online 16-18 September 2020 P. 16-21Abstract: In the paper, a pseudorandom number sequence sensor is considered, its design is based on the Markov model of the simulated process. Such a model is derived from either the theoretical two-dimensional probability density or from the random process samples obtained experimentally. There has been developed a simple high-speed algorithm for operating the sensor using a primary source of pseudorandom numbers with a uniform probability distribution, and statistical simulation of such algorithm has been carried out. It is shown that the obtained sequence of numbers possesses probabilistic and correlation properties that are in good agreement with the specified properties of the simulated random processes. When substituting a hardware random number generator for the source of equiprobable pseudorandom numbers, the sensor generates truly random numbers. The possibilities of the hardware implementation of the introduced algorithm in the form of a pseudorandom (random) number generator are demonstrated.
Библиогр.: с. 21
In the paper, a pseudorandom number sequence sensor is considered, its design is based on the Markov model of the simulated process. Such a model is derived from either the theoretical two-dimensional probability density or from the random process samples obtained experimentally. There has been developed a simple high-speed algorithm for operating the sensor using a primary source of pseudorandom numbers with a uniform probability distribution, and statistical simulation of such algorithm has been carried out. It is shown that the obtained sequence of numbers possesses probabilistic and correlation properties that are in good agreement with the specified properties of the simulated random processes. When substituting a hardware random number generator for the source of equiprobable pseudorandom numbers, the sensor generates truly random numbers. The possibilities of the hardware implementation of the introduced algorithm in the form of a pseudorandom (random) number generator are demonstrated.
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