A single neuron model with memristive synaptic weight

• A single neuron model with memristive synaptic weight is presented to exhibit its kinetic effect. • Memristive single neuron model has time-varying equilibrium points with the change in number. • Complex neuron dynamics is studied using numerical analyses and PCB-based experiments. Synaptic connection weight in neuron is adaptive and memristive synaptic weight can be taken as a changeable connection weight. To exhibit its kinetic effect, a single neuron model with memristive synaptic weight is thereby presented. The memristive single neuron model has time-varying equilibrium points with the changes in number and stability, resulting in the appearance of complex neuron dynamics. Using multiple numerical analyses, complex neuron dynamics is studied in details, including parameter-related dynamics distributions, phase portraits with equilibrium stabilities, and coexisting bifurcation plots. Furthermore, with the analog circuit design, printed-circuit board (PCB)-based experiments are carried out. The physically captured results well validate the numerical ones.