• Journal of the Chungcheong Mathematical Society
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• v.12 no.1
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• pp.119-124
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• 1999

In this paper, T.Kawata's result[2] is generalized, by means of Hausdorff-Young inequality and Beurling's norm.

• Journal of the Korean Mathematical Society
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• v.50 no.6
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• pp.1165-1181
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• 2013

In this paper, we consider a class of periodic It$\hat{o}$ stochastic delay differential equations by using the properties of periodic Markov processes, and some sufficient conditions for the existence of periodic solution of the delay equations are given. These existence theorems improve the results obtained by It$\hat{o}$ et al. [6], Bainov et al. [1] and Xu et al. [15]. As applications, we study the existence of periodic solution of periodic stochastic logistic equation and periodic stochastic neural networks with infinite delays, respectively. The theorem for the existence of periodic solution of periodic stochastic logistic equation improve the result obtained by Jiang et al. [7].

• Journal of the Chungcheong Mathematical Society
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• v.5 no.1
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• pp.103-110
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• 1992

In this paper, T. Kawata's result[2] is generalized, by means of Beurling's norm, in the case of periodic stochastic processes of the second order which belong to Lipschitz class.

• Bulletin of the Korean Mathematical Society
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• v.21 no.2
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• pp.138-138
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• 1984

• Journal of the Chungcheong Mathematical Society
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• v.8 no.1
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• pp.45-53
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• 1995

In this paper, in order to generalize the Theorem[1], it was attempted to generalize the method to prove the Theorem.

• Journal of the Korean Operations Research and Management Science Society
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• v.6 no.2
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• pp.51-55
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• 1981

In both continuous-review and periodic-review non-stationary inventory systems, the non-stationary Poisson demand process and the associated inventory position processes were proved being mutually independent of each other, which lead to the probability distribution of the corresponding net inventory position process in the form of a finite product sum of those two process distributions. It is also discussed how these results can correspond to analytical stochastic inventory cost function formulations in terms of the probability distributions of the processes.