Twister Generator of Arbitrary Uniform Sequences

نویسندگان

  • Aleksei F. Deon
  • Yulian A. Menyaev
چکیده

Twisting generators for pseudorandom numbers may use a congruential array to simulate stochastic sequences. Typically, the computer program controls the quantity of elements in array to limit the random access memory. This technique may have limitations in situations where the stochastic sequences have an insufficient size for some application tasks, ranging from theoretical mathematics and technic constructions to biological and medical studies. This paper proposes a novel approach to generate complete stochastic sequences which don’t need a congruential twisting array. The results of simulation confirm that received random numbers are distributed absolutely uniformly in the set of unique sequences. Moreover, combination of this novel approach with an algorithm of tuning for twisting generation affords the length extension of created sequences without requiring additional computer random access memory.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

On statistical distance based testing of pseudo random sequences and experiments with PHP and Debian OpenSSL

NIST SP800-22 (2010) proposed the state of the art statistical testing techniques for testing the quality of (pseudo) random generators. However, it is easy to construct natural functions that are considered as GOOD pseudorandom generators by the NIST SP800-22 test suite though the output of these functions is easily distinguishable from the uniform distribution. This paper proposes solutions t...

متن کامل

An Area Time Efficient Field Programmable Mersenne Twister Uniform Random Number Generator

Reconfigurable computing offers an attractive solution to accelerating infrared scene simulations. In infrared scene simulations, the modeling of a number of atmospheric and optical phenomena like scintillation, refraction, blurring due to lens optics and photon noise may be implemented in parallel. All of these require simultaneous and continual generation of random numbers. Furthermore, rando...

متن کامل

34.1. Sampling the Uniform Distribution 34.2. Inverse Transform Method

Monte Carlo techniques are often the only practical way to evaluate difficult integrals or to sample random variables governed by complicated probability density functions. Here we describe an assortment of methods for sampling some commonly occurring probability density functions. Most Monte Carlo sampling or integration techniques assume a " random number generator, " which generates uniform ...

متن کامل

34.1. Sampling the Uniform Distribution 34.2. Inverse Transform Method

Monte Carlo techniques are often the only practical way to evaluate difficult integrals or to sample random variables governed by complicated probability density functions. Here we describe an assortment of methods for sampling some commonly occurring probability density functions. Most Monte Carlo sampling or integration techniques assume a " random number generator, " which generates uniform ...

متن کامل

37.1. Sampling the Uniform Distribution 37.2. Inverse Transform Method

Monte Carlo techniques are often the only practical way to evaluate difficult integrals or to sample random variables governed by complicated probability density functions. Here we describe an assortment of methods for sampling some commonly occurring probability density functions. Most Monte Carlo sampling or integration techniques assume a " random number generator, " which generates uniform ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • J. UCS

دوره 23  شماره 

صفحات  -

تاریخ انتشار 2017