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From these we find A, D as before, and compute the deterministic and stochastic bounds.
We propose to give stochastic bounds (both upper and lower bounds) based on convex order.
The difference between the size dependent stochastic bounds and the classical deterministic bounds demonstrates the size effect of RVE.
STAR's model-based predictive GC forward predicts potential patient-specific behavior using the 5th and 95th percentile, choosing an intervention to optimize the placement of these stochastic bounds [28, 33].
This paper presents an approach to provide stochastic bounds for a large class of optimisation problems on graphs when the parameters (i.e. costs, weights or delays) for links are random variables.
It seems unlikely that the signal being located would be completely known, hence we will consider only the deterministic and stochastic bounds (exceptions are cooperative transmitters acting as beacons, or transmitters using standardized waveforms having certain features that are known a priori).
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Using (4.2), (4.4), we can compute the deterministic bound (3.8) and the stochastic bound (3.9).
A stochastic bounded real lemma is then established.
We shall first establish a version of stochastic bounded real lemma (SBRL) which by itself has theoretical importance.
In this paper, at first the stability condition which gives an upper stochastic bound for a class of Stochastic Hybrid Systems (SHS) with deterministic jumps is derived.
Then, by using the Lyapunov Krasovskii functional method and the generalized Itô's formula, both delay-independent and delay-dependent stochastic bounded real lemmas are developed.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com