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Not only does the new theory of the so-called 'dynamic equations' unify the theories of differential equations and difference equations, but it also extends these classical cases to cases 'in between', e.g., to the so-called q-difference equations when T = q N 0, and can be applied to different types of time scales like T = h Z, T = N 0 2, and the space of harmonic numbers T = { H n }.
In particular, it allows to establish important connections between different types of time consistency.
It will be seen that different types of time consistency can be characterized in terms of these concepts.
Different types of time include parts input, for operations and processing, for resources arriving, and time for finished goods or products output are developed for designing manufacturing systems.
The dynamical behaviors such as uniqueness, global asymptotic stability, exponential stability and invariant sets and attractors of the equilibrium point or periodic solutions were investigated for BAM neural networks with different types of time delays (see [28 44, 48]).
In this section, we present examples that illustrate the different types of time consistency for dynamic risk measures and dynamic performance measures, as well as the relationships between them.
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Application to four data sets and a simulation study revealed that the model could potentially be very useful in adequately describing different types of time-to-event data.
In summary, the flexibility provided by the generalized log-logistic model could be very useful in adequately describing different types of time-to-event data.
If we apply this space decomposition procedure to the space W j, we obtain a partition of the high-frequency components, which allows us to identify different types of time-frequency structures.
In Section Simulations, a simulation study is presented to evaluate the performance of generalized log-logistic in comparison with other commonly used PH models to describe different types of time-to-event data.
In summary, our simulation study has demonstrated that the generalized log-logistic could potentially be a very useful parametric model to adequately describe different types of time-to-event data.
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different types of weather
different types of death
different types of substance
different types of safety
different types of regulation
different types of health
different types of sensitivity
different types of content
different types of income
different combinations of time
different intervals of time
different types of application
different types of coffee
different types of accommodation
different types of hardware
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