State Probability

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Ying Chen - One of the best experts on this subject based on the ideXlab platform.

  • reliability analysis of multi State systems subject to failure mechanism dependence based on a combination method
    Reliability Engineering & System Safety, 2017
    Co-Authors: Ying Chen, Zeng Hui Yuan, Ning Tang, Rui Kang
    Abstract:

    A multi-State system is a kind of system in which both the system and its components may display multiple performance levels, and it can be utilized to model more complicated and practical systems. As one kind of multi-State object, the performance degradation of a system and its components can be analyzed in terms of failure mechanism dependence. Some coupling relationships of these failure mechanisms exhibit multi-State properties as well. This paper merged the primary failure mechanism correlations proposed in our previous research and provided a combinational method that proposes a modified binary decision diagram (BDD) and a multi-State multi-valued decision diagram (MMDD) models for the State-Probability evaluation and reliability analysis of the multi-State system. The method consists of four steps: generation of BDD models for components, calculation of State-Probability for components, generation of MMDD models for the system and calculation of reliability for the system. As a study case, the reliability and State-Probability of a multi-State sensor system are evaluated using this combinational method. Finally, a comparison between the binary-State and the multi-State are given as well.

Michael L J Ashford - One of the best experts on this subject based on the ideXlab platform.

Dooseop Eom - One of the best experts on this subject based on the ideXlab platform.

  • performance analysis of binary exponential backoff mac protocol for cognitive radio in the ieee 802 16e m network
    Journal of Industrial and Management Optimization, 2016
    Co-Authors: Shengzhu Jin, Bong Dae Choi, Dooseop Eom
    Abstract:

    We propose a distributed MAC protocol for cognitive radio when primary network is IEEE 802.16e/m WiMAX. Our proposed MAC protocol is the Truncated Binary Exponential Backoff Algorithm where the backoff window size of algorithm is doubled at each collision, and the backoff counter is operated by frame basis in IEEE 802.16e/m and is freezed at a frame with no idle slots. We model our proposed MAC protocol as a 3-dimensional discrete-time Markov chain and obtain steady State Probability of the Markov chain by using a censored Markov chain method. Based on this steady State Probability, we obtain the throughput, packet loss Probability and packet delay distribution of secondary users. Our numerical examples show that the initial contention window size can be determined according to the number of secondary users in order to obtain higher throughput for secondary users, and the maximum backoff window has a large impact on the secondary user's packet loss Probability. Secondary users' packet delay distribution is much influenced by the initial contention window size and the number of secondary users.

  • performance analysis of binary exponential backoff mac protocol for cognitive radio in the ieee 802 16e m network
    International Conference on Queueing Theory and Network Applications, 2016
    Co-Authors: Shengzhu Jin, Bong Dae Choi, Dooseop Eom
    Abstract:

    We propose a distributed MAC protocol for cognitive radio when primary network is IEEE 802.16e/m WiMAX. Our proposed MAC protocol is Truncated Binary Exponential Backoff Algorithm where backoff stage of algorithm is doubled at each collision, and backoff counter is operated by frame basis and is freezed at a frame with no idle slots. We model our proposed MAC protocol as a 3-dimensional discrete-time Markov chain and obtain steady State Probability of the Markov chain by using a censored Markov chain method. Based on this steady State Probability, we obtain the throughput, packet loss Probability and packet delay distribution of secondary users. Our numerical examples show that initial contention window size can be determined according to the number of secondary users in order to obtain higher throughput for secondary users, and the maximum backoff stage has a large impact on the secondary user’s packet loss Probability.

Rui Kang - One of the best experts on this subject based on the ideXlab platform.

  • reliability analysis of multi State systems subject to failure mechanism dependence based on a combination method
    Reliability Engineering & System Safety, 2017
    Co-Authors: Ying Chen, Zeng Hui Yuan, Ning Tang, Rui Kang
    Abstract:

    A multi-State system is a kind of system in which both the system and its components may display multiple performance levels, and it can be utilized to model more complicated and practical systems. As one kind of multi-State object, the performance degradation of a system and its components can be analyzed in terms of failure mechanism dependence. Some coupling relationships of these failure mechanisms exhibit multi-State properties as well. This paper merged the primary failure mechanism correlations proposed in our previous research and provided a combinational method that proposes a modified binary decision diagram (BDD) and a multi-State multi-valued decision diagram (MMDD) models for the State-Probability evaluation and reliability analysis of the multi-State system. The method consists of four steps: generation of BDD models for components, calculation of State-Probability for components, generation of MMDD models for the system and calculation of reliability for the system. As a study case, the reliability and State-Probability of a multi-State sensor system are evaluated using this combinational method. Finally, a comparison between the binary-State and the multi-State are given as well.

Abhishek Dhar - One of the best experts on this subject based on the ideXlab platform.

  • steady State of an active brownian particle in a two dimensional harmonic trap
    Physical Review E, 2020
    Co-Authors: Kanaya Malakar, Anupam Kundu, Arghya Das, Vijay K Kumar, Abhishek Dhar
    Abstract:

    We find an exact series solution for the steady-State Probability distribution of a harmonically trapped active Brownian particle in two dimensions in the presence of translational diffusion. This series solution allows us to efficiently explore the behavior of the system in different parameter regimes. Identifying "active" and "passive" regimes, we predict a surprising re-entrant active-to-passive transition with increasing trap stiffness. Our numerical simulations validate this finding. We discuss various interesting limiting cases wherein closed-form expressions for the distributions can be obtained.