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The influence of the agitation rate, the viscosity of the dispersed phase, the molecular weight of the polymer and the volume ratio between the dispersed phase and the continuous one on the drug release rate has been studied.
However, an issue of the joint proof of such a property on a general time scale (including the continuous one) seems to be a difficult task.
A continuous random variable may be characterized either by its probability density function (pdf), moment generating function (mgf), moments, hazard rate function etc. Basically cconstruction of a discrete analogue from a continuous distribution is based on the principle of preserving one or more characteristic property of the continuous one.
In contrast to the ISO segmented method, the continuous one is roughness-scale independent.
The transformation method allows to transform the mixed optimization problem into the continuous one.
In Section 2, we present the discrete mathematical model derived from the continuous one by using backward Euler discretization.
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Consider the continuous one-parameter group of diffeomorphisms R ∋ t ↦ σ t.
LetAi=dU ai) denote the infinitesimal generator of the continuous one-parameter groupt↦U exp −tai)) and setAα=Ai1 …Ainwhereα=(i1, …, in) withij∈{1, …, d′}.
Moreover, discrete time models, governed by difference equations, are more appropriate than the continuous ones.
Petri nets are used to model the discrete aspects and differential equation systems are used for the continuous ones.
Results confirm that imposing the proposed conditions makes discrete filters properties consistent with those of the continuous ones.
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