Similarly, below I analyze the synchronization of stock price volatility.
It is worth pointing out that the presented methods cannot be applied to analyze the synchronization of two nonidentical chaotic neural networks with time-varying delays.
In summary, we present an efficient theoretical method for analyzing the synchronization of genetic oscillator networks, which is helpful for understanding and testing the synchronization phenomena in biological organisms.
In this section we have analyzed the synchronization properties of the model, and also its relation with the underlying network structure.
Following the above discussion that synchronization plays a major role in the processing of high level information, it would be important to analyze the synchronization behavior of these networks in relation to their modular and hierarchical organization.
In the following section we will analyze the synchronization properties of the system.
Hence, it is necessary to analyze the synchronization control problem of complex networks with unknown target node.
Regional homogeneity (ReHo) is a data driven method which can be applied to process the resting state fMRI data through analyzing the temporal synchronization of the inter-regional fMRI signals of the whole brain [ 21].
Regional homogeneity (ReHo), a novel method that measures the functional connectivity, has been developed to analyze the local synchronization of spontaneous fMRI BOLD signals, reflecting the coherence of spontaneous neuronal activity [ 8].
Finally, we analyze the partial synchronization of the excitatory inhibitory network given by (74), (75), and (76) with the activation function given by (52) in the face of increasing inhibitory time constants.
