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D. Opris

  1. The analysis of stochastic stability of stochastic models that describe tumor-immune systems.

    Wed, 09/09/2009 - 22:08 — SomNambul
    Authors: D. Opris, A. Sandru, O. Chis
    Subjects: Dynamical Systems
    Abstract

    In this paper we investigate some stochastic models for tumor-immune systems.
    To describe these models, we used a Wiener process, as the noise has a
    stabilization effect. Their dynamics are studied in terms of stochastic
    stability in the equilibrium points, by constructing the Lyapunov exponent,
    depending on the parameters that describe the model. Stochastic stability was
    also proved by constructing a Lyapunov function. We have studied and and
    analyzed a Kuznetsov-Taylor like stochastic model and a Bell stochastic model
    for tumor-immune systems.

  2. The analysis of stochastic stability of stochastic models that describe tumor-immune systems.

    Wed, 09/09/2009 - 22:08 — SomNambul
    Authors: D. Opris, A. Sandru, O. Chis
    Subjects: Dynamical Systems
    Abstract

    In this paper we investigate some stochastic models for tumor-immune systems.
    To describe these models, we used a Wiener process, as the noise has a
    stabilization effect. Their dynamics are studied in terms of stochastic
    stability in the equilibrium points, by constructing the Lyapunov exponent,
    depending on the parameters that describe the model. Stochastic stability was
    also proved by constructing a Lyapunov function. We have studied and and
    analyzed a Kuznetsov-Taylor like stochastic model and a Bell stochastic model
    for tumor-immune systems.

  3. The analysis of the stochastic stability for an economic game.

    Tue, 09/08/2009 - 12:16 — SomNambul
    Authors: M. Neamtu, D. Opris, A. L. Ciurdariu, A. Sandru
    Subjects: Dynamical Systems
    Abstract

    In this paper we investigate a stochastic model for an economic game. To
    describe this model we have used a Wiener process, as the noise has a
    stabilization effect. The dynamics are studied in terms of stochastic stability
    in the stationary state, by constructing the Lyapunov exponent, depending on
    the parameters that describe the model. Also, the Lyapunov function is
    determined in order to analyze the mean square stability. The numerical
    simulation that we did justifies the theoretical results.

  4. Stochastic generalized fractional HP equations and applications.

    Tue, 09/01/2009 - 12:47 — SomNambul
    Authors: I. D. Albu, M. Neamtu, D. Opris
    Subjects: Dynamical Systems
    Abstract

    In this paper we established the condition for a curve to satisfy stochastic
    generalized fractional HP (Hamilton-Pontryagin) equations. These equations are
    described using Ito integral. We have also considered the case of stochastic
    generalized fractional Hamiltonian equations, for a hyperregular Lagrange
    function. From the stochastic generalized fractional Hamiltonian equations,
    Langevin generalized fractional equations were found and numerical simulations
    were done.

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