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The paper proposes novel ways to analyse and model such systems in terms of waves.
To accurately model such systems, it is necessary to keep track of a large number of particles.
We will discuss how to properly model such systems and will suggest effective tradeoffs between reliability, simulation speed, and accuracy.
Nowadays, it is a common practice to model such systems in the framework of stochastic hybrid system models.
We model such systems as linear impulsive systems and we apply our theorem to the analysis and state-feedback stabilization.
Finite element models do not suffer from these limitations at low frequencies and can be used to model such systems "exactly".
Similar(50)
However, this causes a practical difficulty in modelling such systems.
First, we describe different levels of abstraction for modeling such systems and how their speed and accuracy relate.
This poses challenges for understanding and modeling such systems, yet modeling is often the only option to study them.
Modeling such systems requires solving the associated Fokker-Planck equation subject to an absorbing barrier.
Over the last decade considerable research has been published on agglomeration and associated techniques for characterising and modelling such systems.
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