• Title/Summary/Keyword: random sequences

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Fast Generation of Binary Random Sequences by Use of Random Sampling Method

  • Harada, Hiroshi;Kashiwagi, Hiroshi
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10b
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    • pp.240-244
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    • 1992
  • A new method for generation of binary random sequences, called random sampling method, has been proposed by the authors. However, the random sampling method has the defect that binary random sequence can not be rapidly generated. In this paper, two methods based on the random sampling method are proposed for fast generation of binary random sequences. The optimum conditions for obtaining ideal binary random sequences are derived.

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APPROXIMATING RANDOM COMMON FIXED POINT OF RANDOM SET-VALUED STRONGLY PSEUDO-CONTRACTIVE MAPPINGS

  • LI JUN;HUANG NAN JING
    • Journal of applied mathematics & informatics
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    • v.17 no.1_2_3
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    • pp.329-341
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    • 2005
  • In this paper, we introduce new random iterative sequences with errors approximating a unique random common fixed point for three random set-valued strongly pseudo-contractive mappings and show the convergence of the random iterative sequences with errors by using an approximation method in real uniformly smooth separable Banach spaces. As applications, we study the existence of random solutions for some kind of random nonlinear operator equations group in separable Hilbert spaces.

On desirable conditions for a random number used in the random sampling method

  • Harada, Hiroshi;Kashiwagi, Hiroshi;Takada, Tadashi
    • 제어로봇시스템학회:학술대회논문집
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    • 1990.10b
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    • pp.1295-1299
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    • 1990
  • A new method called random sampling method has been proposed for generation of binary random sequences. In this paper, a new concept, called merit factor Fn, is proposed for evaluating the randomness of the binary random sequences generated by the random sampling method. Using this merit factor Fn, some desirable conditions are investigated for uniform random numbers used in the random sampling method.

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Random number generation by use of de Bruijin sequence

  • Harada, Hiroshi;Kashiwagi, Hiroshi;Oguri, Kazuo
    • 제어로봇시스템학회:학술대회논문집
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    • 1988.10b
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    • pp.1033-1036
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    • 1988
  • This paper proposes a new method for generation of uniform random numbers using binary random sequences. These binary sequences are obtained from a de Bruijn sequence by random sampling method. Several statistical tests are carried out for the random numbers generated by the proposed method, and it is shown that the random numbers have good random properties.

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Almost Sure Convergence for Asymptotically Almost Negatively Associated Random Variable Sequences

  • Baek, Jong-Il
    • Communications for Statistical Applications and Methods
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    • v.16 no.6
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    • pp.1013-1022
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    • 2009
  • We in this paper study the almost sure convergence for asymptotically almost negatively associated(AANA) random variable sequences and obtain some new results which extend and improve the result of Jamison et al. (1965) and Marcinkiewicz-Zygumnd strong law types in the form given by Baum and Katz (1965), three-series theorem.

Generation of Finite Inductive, Pseudo Random, Binary Sequences

  • Fisher, Paul;Aljohani, Nawaf;Baek, Jinsuk
    • Journal of Information Processing Systems
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    • v.13 no.6
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    • pp.1554-1574
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    • 2017
  • This paper introduces a new type of determining factor for Pseudo Random Strings (PRS). This classification depends upon a mathematical property called Finite Induction (FI). FI is similar to a Markov Model in that it presents a model of the sequence under consideration and determines the generating rules for this sequence. If these rules obey certain criteria, then we call the sequence generating these rules FI a PRS. We also consider the relationship of these kinds of PRS's to Good/deBruijn graphs and Linear Feedback Shift Registers (LFSR). We show that binary sequences from these special graphs have the FI property. We also show how such FI PRS's can be generated without consideration of the Hamiltonian cycles of the Good/deBruijn graphs. The FI PRS's also have maximum Shannon entropy, while sequences from LFSR's do not, nor are such sequences FI random.

Binary random sequence generation by use of random sampling of M-sequence

  • Hiroshi Harada;Hiroshi Kashiwagi;Satoshi Honda;Kazuo Oguri
    • 제어로봇시스템학회:학술대회논문집
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    • 1987.10a
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    • pp.832-835
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    • 1987
  • This paper proposes a new method of generating binary random sequences using a randomly sampled M-sequence. In this paper two methods of sampling are proposed. Expected values of the autocorrelation function of the sequence generated by these methods are calculated theoretically. From the results of computer simulation, it is shown that using these methods, we can get binary random sequences which have good random properties.

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Evaluation of randomness of binary random sequence

  • Harada, Hiroshi;Kashiwagi, Hiroshi;Takada, Tadashi
    • 제어로봇시스템학회:학술대회논문집
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    • 1989.10a
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    • pp.979-983
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    • 1989
  • This paper proposes a new concept, called merit factor Fr, for evaluating the randomness of binary random sequences. The merit factor Fr is obtained from the expected values of the autocorrelation function of the binary random sequence. Using this merit factor Fr, randomness of the binary random sequences generated by the random sampling method is evaluated.

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CLASSIFICATION OF QUASIGROUPS BY RANDOM WALK ON TORUS

  • MARKOVSKI SMILE;GLIGOROSKI DANILO;MARKOVSKI JASEN
    • Journal of applied mathematics & informatics
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    • v.19 no.1_2
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    • pp.57-75
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    • 2005
  • Quasigroups are algebraic structures closely related to Latin squares which have many different applications. There are several classifications of quasigroups based on their algebraic properties. In this paper we propose another classification based on the properties of strings obtained by specific quasigroup transformations. More precisely, in our research we identified some quasigroup transformations which can be applied to arbitrary strings to produce pseudo random sequences. We performed tests for randomness of the obtained pseudo-random sequences by random walks on torus. The randomness tests provided an empirical classification of quasigroups.