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Figure 3 Adaptive measurement process illustration.
In this article, we present an adaptive measurement method for a large-area SPM.
Such an adaptive measurement process requires a system modeling based on the continuous learning of the environment feedback.
The adaptive measurement aggregation is a mechanism with which the DMR decides the measurement parameters to be reported to the S-DeNB.
The involvement of torch nodes and adaptive measurement aggregation mechanism module has significantly contributed in decreasing the failure probability as the distance increases.
To overcome this challenge, a novel methodology for adaptive measurement and modelling of data captured by in-line 3D surface measurement systems is proposed in this paper.
Based on velocity readings from IMU, the OPU provides a mobility-based adaptive measurement aggregation mechanism of values collected by TNs and DMRs to generate periodic- or event-based measurement report.
The proposed scheme involves the following key features: (1) torch nodes to effectively forecast target DeNBs, (2) adaptive measurement aggregation based on mobility and (3) distributed mobile relays with load balancer for efficient resource utilization.
This paper proposes a novel scheme to enhance the quality of service in high-speed railway (HSR) communication environment using the concept of torch nodes (TNs) and adaptive measurement aggregation (AMA).
Third, both adaptive state feedback and adaptive measurement output feedback controllers are synthesized to solve the cooperative output regulation problem without the assumption that each follower knows the system matrix of the leader system.
The AS is achieved by designing an adaptive measurement matrix used in CS based on the energy distribution characteristics of image in DCT domain, which has a good effect in enhancing the CS performance.
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