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In traditional approaches the synchronization of matrix access by different threads is done, e.g., by the standard lock mechanism of Java.
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It can be seen that as time index increases, mean square time synchronization error approaches the steady-state value when utilizing SO-DCTS algorithm with Gaussian delay.
Because synchronization indices in these pairs approached the "ceiling" of synchronization, variability across all electrode pairs has the same interpretation: less variability means increase of synchronization and more variability means decrease of synchronization.
This paper presents a model reference adaptive control approach for the synchronization of a discrete-time chaotic systems using output tracking control.
In this paper, a kind of control approach about the synchronization of fractional-order and integer-order chaotic (hyper-chaotic) systems with different dimensions is proposed.
The numerical simulations clearly verify the effectiveness of the developed sliding mode control approach to the synchronization of nonidentical two chaotic neural networks with discrete and distributed time-varying delays as well as leakage delay.
Among the synchronization approaches available for OFDM, data-aided methods allow the use of both autocorrelation and cross-correlation properties, and one-shot synchronization can be achieved in bit pipe and burst communications.
By using the adaptive control approach, the exponential synchronization in the p th moment of neutral-type delayed neural networks is investigated in [26].
By using the adaptive pinning approach, the robust synchronization of a class of nonlinearly coupled complex networks is investigated in [20].
This study proposes an approach that measures the synchronization strength of bivariate non-stationary nonlinear data against phase differences.
The proposed approach consists of the synchronization phase and the tracking phase.
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