Synchronization of chaotic neuronal oscillators (Q1809636)

The paper deals with noise-induced synchronization of chaotic neurotic maps with different initiations. Noise can be important for stochastic resonance to enhance the signal detection sensitivity in a chaotic neural network and can even lead to a complete synchronization of uncoupled maps. The stability of the noise-induced synchronization in a network of uncoupled oscillators depends directly on the Lyapunov exponent of the oscillator under the effect of noise. The authors show that when noise is added to the control parameter of the system a set of related systems arises and the final trajectories of different initial values are governed by every system in this set. A detailed explanation of this noise-induced synchronization and numerical results for chaotic neuron models are given. Furthermore, the so-called changeable chaotic systems are introduced and the theory is extended to general chaotic systems.