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It is unknown whether encounters with cars to steal follow a Poisson process (Assumption 3).
However, if the equivalence of biological process assumption is denied, or simply doubted, one can argue for the opposing position.
A switching-type fuzzy neural networks (STFNNs) model is proposed which captures external disturbances, sensor nonlinearities, and mode switching phenomenon of the fuzzy neural networks without the Markovian process assumption.
It is considered that a production line where the probability of a transition will undergo from one state to another state depends only on the current state of the line (Markov process assumption).
The accuracy of the linear Cahn Hilliard Cook (CHC) theory in matrix form (multicomponent description) is scrutinized by comparing its exact macroscopic derivation with its phenomenological derivation based on the linear Markov process assumption.
Under the homogeneous Poisson process assumption, the distribution of the sample-POM, estimated from a finite sample of n bins, is asymptotically normal with zero mean and variance of 2/n.
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We propose the concept of building thermal autonomy and a two-step process assumption-based design method.
The first step of the process assumption-based design method aims for the determination of building thermal qualities for a thermally autonomous building.
In two earlier papers we proposed a process assumption-based design method, one aim of which is the determination of the thermal requirement of a building by investigating the building functioning as a dynamic thermal system.
All MC simulations are run on linear combiners and thus satisfy the driving process assumptions A1a and A1b.
However, in order to guarantee independence of vectors u k,u k−1,… we have to impose a second condition on the driving process: Driving process assumptions (A1b): Assume the driving process u k being generated by a linearly filtered process x k as described above.
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