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Showing 1 to 10 of 10 for “"Continuous-time Markov chains"”.

  1. Reciprocal classes of continuous time Markov Chains

    In this thesis we study reciprocal classes of Markov chains. Given a continuous time Markov chain on a countable state space, acting as reference dynamics, the associated reciprocal class is the set of all probability measures on path space that can be written as a mixture of its bridges. These …

    potsdam-diss Repository record for Reciprocal classes of continuous time Markov Chains (opens in a new tab)

  2. Specification and verification of systems using model checking and Markov reward models

    This thesis examines Markov reward models, a formalism based on continuous time Markov chains, and it's usage in the generation and analysis of service levels. The particular solution technique we employ in this thesis is model checking, using Continuous Reward Logic as a means to specify …

    cape-town Repository record for Specification and verification of systems using model checking and Markov reward models (opens in a new tab)

  3. Probabilistic reasoning and inference for systems biology

    … are a novel modelling approach using continuous time Markov chains that enables deductive derivation of model behaviours and their properties, and the application of Bayesian inferential methods to solve the inverse problem of model inference and comparison, given uncertain knowledge …

    glasgow Repository record for Probabilistic reasoning and inference for systems biology (opens in a new tab)

  4. Approximation and System Identification Techniques for Stochastic Biomolecular Systems

    … models of chemical reaction networks, given by continuous time Markov chains with countably infinite state spaces, creates computational and analytical difficulties when performing analysis or system identification. Therefore, approximate models that exploit timescale separation between …

    mit Repository record for Approximation and System Identification Techniques for Stochastic Biomolecular Systems (opens in a new tab)

  5. Statistical verification and differential privacy in cyber-physical systems

    … techniques are performed on both Discrete-Time and Continuous-Time Stochastic Hybrid Systems to reduce them to Discrete-Time Markov Chains and Continuous-Time Markov Chains, respectively; and statistical verification algorithms are proposed to verify Linear Inequality LTL and Metric …

    uiuc Repository record for Statistical verification and differential privacy in cyber-physical systems (opens in a new tab)

  6. Controlling Molecular-Scale Motion: Exact Predictions for Driven Stochastic Systems

    … pumps: stochastic systems that are driven by time-dependent perturbations. A number of exact theoretical predictions have been made recently describing how stochastic pumps respond to arbitrary driving. This work investigates one such prediction, the current decomposition formula, and its …

    maryland Repository record for Controlling Molecular-Scale Motion: Exact Predictions for Driven Stochastic Systems (opens in a new tab)

  7. Large deviations of stochastic systems and applications

    … identification. It encompasses analysis of two-time-scale Markov processes and system identification with regular and quantized data. First, we develops large deviations principles for systems driven by continuous-time Markov chains with twotime scales and related optimal control problems. A …

    wayne-thes Repository record for Large deviations of stochastic systems and applications (opens in a new tab)

  8. A path-based framework for analyzing large markov models

    … on the solutions of transient measures in large continuous-time Markov chains (CTMCs). It extends existing path-based and uniformization-based methods by identifying sets of paths that are equivalent with respect to a reward measure and related to one another via a simple structural relationship. …

    uiuc Repository record for A path-based framework for analyzing large markov models (opens in a new tab)

  9. Applications of jump processes in epidemiology and neuroscience

    … models the occurrence of discrete events over time. In epidemiology, the events correspond to catching an infection, recovering from a disease, etc. In neuroscience, the spike train of a neuron can be described as a jump process. The first contribution of this thesis is a data-informed approach …

    uiuc Repository record for Applications of jump processes in epidemiology and neuroscience (opens in a new tab)

  10. Stochastic processes in T-cell signaling

    … such as escapes from stable basins, take a long time (waiting time) to occur, they take little time to complete once they have started. We showed that for Markov processes characterized by detailed balance, successful transitions, on average, complete exactly as quickly as transitions in the …

    mit Repository record for Stochastic processes in T-cell signaling (opens in a new tab)