A family of coexisting multi-scroll chaos and its selected control in coupled non-oscillatory neurons: A case study.

This study presents a family of coexisting multi-scroll chaos in a network of coupled non-oscillatory neurons. The dynamics of the system are analyzed using phase portraits, basins of attraction, time series, bifurcation diagrams, and spectra of Lyapunov exponents. The coexistence of multiple bifurcation diagrams leads to a complex pattern of multi-scroll formation, which is further complicated by the presence of coexisting single-scroll attractors that merge to form multi-scroll chaos.

Effects of bias current and control of multistability in 3D hopfield neural network.

This work studies the dynamics of a three dimensional Hopfield neural network focusing on the impact of bias terms. In the presence of bias terms, the models displays an odd symmetry and experiences typical behaviors including period doubling, spontaneous symmetry breaking, merging crisis, bursting oscillation, coexisting attractors and coexisting period-doubling reversals as well. Multistability control is investigated by employing the linear augmentation feedback strategy.

Control and symmetry breaking aspects of a geomagnetic field inversion model.

In this work, we consider the geomagnetic field inversion model proposed by Gissinger et al. [Europhys. Lett.

Four-scroll attractor on the dynamics of a novel Hopfield neural network based on bi-neurons without bias current.

The dynamics of a neural network under several factors (bias current and electromagnetic induction effect) are recently used to simulate activities of the brain under different excitation. In this paper, we introduce a novel Hopfield neural network (HNN) based on two neurons with a memristive synaptic weight connected between neuron one and two based of flux controlled memristor recently proposed by Hua M. et al.