• Title/Summary/Keyword: Deterministic

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POSSIBLE EDGES OF A FINITE AUTOMATON DEFINING A GIVEN REGULAR LANGUAGE

  • Melnikov, B.F.;Sciarini Guryanova, N.V.
    • Journal of applied mathematics & informatics
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    • v.9 no.2
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    • pp.645-655
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    • 2002
  • In this Paper we consider non-deterministic finite Rabin-Scott's automata. We define special abstract objects, being pairs of values of states-marking functions. On the basis of these objects as the states of automaton, we define its edges; the obtained structure is considered also as a non-deterministic automaton. We prove, that any edge of any non-deterministic automaton defining the given regular language can be obtained by such techniques. Such structure can be used for solving various problems in the frames of finite automata theory.

Optimum Design of the Brushless Motor Considering Parameter Tolerance (설계변수 공차를 고려한 브러시리스 모터 출력밀도 최적설계)

  • Son, Byoung-Ook;Lee, Ju
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.59 no.9
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    • pp.1600-1604
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    • 2010
  • This paper presents the optimum design of the brushless motor to maximize the output power per weight considering the design parameter tolerance. The optimization is proceeded by commercial software that is adopted the scatter-search algorithm and the characteristic analysis is conducted by FEM. The stochastic optimum design results are compared with those of the deterministic optimization method. We can verify that the results of the stochastic optimization is superior than that of deterministic optimization.

Fractional Integration in the Context of Deterministic Trends

  • Gil-Alana, L.A.
    • Communications for Statistical Applications and Methods
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    • v.11 no.2
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    • pp.313-321
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    • 2004
  • In this article we show that the tests of Robinson (1994) may have serious problems in distinguishing between fractionally integrated processes in the context of deterministic trends. The results are obtained via Monte Carlo experiments. A simple procedure, based on the t-values of the coefficients from the differenced regression, is presented to correctly specify the time series of interest and, an empirical application, using data of the US GNP is also carried out at the end of the article.

EDGE-MINIMIZATION OF NON-DETERMINISTIC FINITE AUTOMATA

  • Melnikov, B.F.;Melnikova, A.A.
    • Journal of applied mathematics & informatics
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    • v.8 no.3
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    • pp.693-703
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    • 2001
  • In this paper we consider non-deterministic finite Rabin-Scott’s automata. We use a special structure to descibe all the possible edges of non-determinstic finite automaton defining the given regular language. Such structure can be used for solving various problems of finite automata theory. One of these problems is edge-minimization of non-deterministic automata. As we have not touched this problem before, we obtain here two versions of the algorithm for solving this problem to continue previous series of articles.

Segmentation of Color Image Using the Deterministic Anneanling EM Algorithm (결정적 어닐링 EM 알고리즘을 이용한 칼라 영상의 분할)

  • 박종현;박순영;조완현
    • Proceedings of the IEEK Conference
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    • 1999.11a
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    • pp.569-572
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    • 1999
  • In this paper we present a color image segmentation algorithm based on statistical models. A novel deterministic annealing Expectation Maximization(EM) formula is derived to estimate the parameters of the Gaussian Mixture Model(GMM) which represents the multi-colored objects statistically. The experimental results show that the proposed deterministic annealing EM is a global optimal solution for the ML parameter estimation and the image field is segmented efficiently by using the parameter estimates.

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A study on the Performance Evaluation of Flexible Manufacturing Systems (유연생산시스템의 성능평가에 관한 연구)

  • 장진익;김원중
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.23 no.61
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    • pp.13-22
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    • 2000
  • To apply the queueing network theory in evaluating performances of flexible manufacturing systems, it is generally assumed that the processing times are distributed exponentially. However, in FMS, processing times are usually deterministic. In this study the performance measures of FMS are approximated under the assumption that processing times are usually deterministic. Multi-classes of parts and single server and multi-server stations are considered in the model. This study also that, in the numerical example, this approach yields better solutions than those obtained by the pure Linearizer algorithm, when the processing times are deterministic.

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Identification of Chaos Phenomenon using the Classical Nonparametric Tests

  • Park, Young-Sun;Choi, Hang-Suk;Choi, Eun-Sun;Park, Moon-Il;Oh, Jae-Eung;Cha, Kyung-Joon
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.1
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    • pp.95-113
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    • 2006
  • The data resulting from a deterministic dynamic system may often appear to be random. However, it is important to distinguish a deterministic and a random processes for statistical analysis. In this paper, we propose a nonparametric test procedure to distinguish a noisy chaos from i.i.d. random process. The proposed procedure can be easily implemented by computer. We notice that the test is very effective to identify a low dimensional chaos process in some cases.

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STOCHASTIC DIFFERENTIAL EQUATION MODELS FOR EXTRACELLULAR SIGNAL-REGULATED KINASE PATHWAYS

  • Choo, S.M.;Kim, Y.H.
    • Journal of applied mathematics & informatics
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    • v.31 no.3_4
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    • pp.457-467
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    • 2013
  • There exist many deterministic models for signaling pathways in systems biology. However the models do not consider the stochastic properties of the pathways, which means the models fit well with experimental data in certain situations but poorly in others. Incorporating stochasticity into deterministic models is one way to handle this problem. In this paper the way is used to produce stochastic models based on the deterministic differential equations for the published extracellular signal-regulated kinase (ERK) pathway. We consider strong convergence and stability of the numerical approximations for the stochastic models.

A Deterministic Method of Large Prime Number Generation (결정론적인 소수 생성에 관한 연구)

  • Park, Jung-Gil;Park, Bong-Joo;Baek, Ki-Young;Chun, Wang-Sung;Ryou, Jae-Cheol
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.9
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    • pp.2913-2919
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    • 2000
  • It is essential to get large prime numbers in the design of asymmetric encryption algorithm. However, the pseudoprime numbers with high possibility to be primes have been generally used in the asymmetric encryption algorithms, because it is very difficult to find large deterministic prime numbers. In this paper, we propose a new method of deterministic prime number generation. The prime numbers generated by the proposed method have a 100% precise prime characteristic. They are also guaranteed reliability, security strength, and an ability of primitive element generation.

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Multi-Objective Stochastic Optimization in Water Resources System

  • Shim, Soon Bo
    • Journal of the Korean Operations Research and Management Science Society
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    • v.8 no.1
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    • pp.41-59
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    • 1983
  • The purpose of this paper is to present a method of multi-objective, stochastic optimization in water resources system which investigates the development of potential non-normal deterministic equivalents for subsequent use in multiobjective stochastic programming methods, Given probability statement involving a function of several random variables, it is often possible to obtain a deterministic equivalent of it that does not include any orginal random variables. A Stochastic trade-off technique-MSTOT is suggested to help a decision maker achieve satisfactory levels for several objective functions. This makes use of deterministic equivalents to handle random variables in the objective functions. The emphasis is in the development of non-normal deterministic equivalents for use in multiobjective stochastic techniques.

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