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In this work, we present a state dependent sampling control that maximizes the sampling intervals of state feedback control.
For discrete-time multi-agent systems with communication delays, a distributed sampling control protocol applying individual local information is proposed.
The event-triggered sampling control scheme is motivated by applications of embedded microprocessors with limited computation and storage resources.
Considering the uniqueness of farms, an object-oriented farm model was developed to describe farm objects properly, edit sampling plan conveniently, and perform sampling control easily.
This paper investigates the global asymptotic stability and stabilization of memristive neural networks (MNNs) with communication delays via event-triggered sampling control.
Then, the obtained results are extended to design the sampling map in three dynamic sampling control situations: event-triggered control, self-triggered control, and state-dependent sampling.
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Gregoire et al. (1995) have proposed a number of sampling procedures (randomized branch sampling, importance sampling, control-variate sampling, two-stage and three-stage sampling) that can be used to estimate foliage and other characteristics of individual trees.
The bias could theoretically be controlled by sampling controls only from the reservoir of susceptible individuals.
Sample control program.
Test samples, control and loperamide were given orally by means of a feeding needle.
Five different models were built: Inflamed samples, non-inflamed samples, control samples, CD samples, and all samples.
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