A novel hardware-efficient auditory neuron model based on ergodic cellular automaton and its first pitch-shift effect

In this paper, a novel hardware-efficient auditory neuron model whose nonlinear dynamics is described by an ergodic cellular automaton is proposed. It is shown that the proposed model can reproduce first pitch-shift effect, which is one of the nonlinear sound processing functions observed in the biological auditory system. The proposed model and an ordinary differential equation (ODE) model based on generic threshold-plus-reinjection dynamics are implemented on field-programmable gate arrays (FPGAs) and it is demonstrated that the proposed model employs fewer circuit elements for FPGA implementation and consumes lower power than the ODE model.