Biomedical subjects
Publications and source records attributed to W Yinghai.
Parallel dynamics of neural networks with separable coupling is given starting from Coolen-Sherrington theory. Away from saturation, it is shown that this parallel retrieve dynamics is equivalent to the sequential dynamics for finite temperature. But the finite-size effects were found to be governed by a homogeneous Markov process, not by a time-dependent Ornstein-Uhlenbeck process in sequential dynamics.
In order to excite experimentalists to apply a dynamical control method [Zhao et al., Phys. Rev. E 53, 299 (1996); 57, 5358 (1998)], we further introduce a simplified control law in this paper. The law provides a convenient way (in certain circumstance a necessary way) for experimentalists to achieve the system control when the exact position of the desired control objective cannot be known in advance. The validity of the control law is rigidly verified when the system nears a bifurcation point but our numerical examples show that it can be extended to a wide parameter region practically.
We present a predictor-feedback method for synchronizing chaotic systems in this paper. By using this method, two structurally equivalent or nonequivalent systems can be synchronized very effectively and quickly. Moreover, the feedback perturbation can be switched on even if trajectories of the two systems are far from each other. Therefore, this method is applicable to real-world experimental systems, especially to some fast experimental systems. The validity of this method is demonstrated by synchronizing hyperchaotic harmonics in a time-delay system. As an application, we introduce how messages can be encoded, transmitted, and decoded using this technique. We suggest taking use of the multistability of time-delay systems to improve the performance of the secure communication.
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