Abstract
A variable boostable chaotic system and the Hindmarsh–Rose neuron model are applied for observing the dynamics revised by memristive computation. Nonlinearity hidden in a memristor makes a dynamic system prone to be chaos. Inherent dynamics in a dynamic system can be preserved in specific circumstances. Specifically, as an example, offset boosting in the original system is inherited in the derived memristive system, where the average value of the system variable is rescaled linearly by the offset booster. Additional feedback from memristive computation raises chaos, as a case, in the Hindmarsh–Rose neuron model the spiking behavior of membrane potential exhibits chaos with a relatively large parameter region of the memristor.
Highlights
Memristor is a new nonlinear component that brings great convivence for chaos generation [1–5] and dynamics control [6–10]
Offset controller e only rescales the average value of y without influencing system dynamics
Memristor and memristive computation have great merits for producing chaos and dynamics control due to the special nonlinearity. It shows that even a memristor function is a linear function, the memory effect from memristive computation still returns chaos under a specific bifurcation
Summary
Memristor is a new nonlinear component that brings great convivence for chaos generation [1–5] and dynamics control [6–10]. It can be seen from the figure that the system has a couple of periodic windows. From Lyapunov exponents and bifurcation, we observe that the system undergoes a typical inverse-period-doubling process from chaos. Offset controller e only rescales the average value of x without influencing system dynamics
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