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To focus on synchronization, the channel frequency response used for channel equalization is assumed to be perfectly known at the receiver.
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Recently, many works have focused on synchronization induced by more realistic complex network systems with the small-world property, the scale-free degree distribution, and the modular hierarchical structure [ 11, 19, 20].
We focus on the synchronization degree the parameter from graph theory that describes the richness of connectivity (based on oscillatory phase synchronization) that each electrode has with other electrodes.
The discussion is centered on the modeling procedures of repetitive processes with the special focus on the synchronization of resources and workflow continuity, which is crucial in scheduling and managing repetitive projects.
However, these papers mainly focus on the synchronization in mean square.
One is that there are few works focus on the synchronization of FONNs by means of observer.
In this work, we mainly focus on the synchronization schemes proposed for DRM, where the receiver has the full knowledge of the pilot cell position and phase.
The robustness test consists of two categories: one is focused on frame synchronization, and the other is concerned with watermark recovery.
The three basic models focus on improving the synchronization accuracy, so their synchronization overheads are usually very large.
This paper focuses on chaos synchronization.
This paper focuses on the synchronization control methodology for a class of delayed reaction diffusion memristor-based neural networks.
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