Robustness in binary cellular non-linear networks analog VLSI resonate-and-fire neuron

This paper is devoted to the study of robustness in binary resonate-and-fire neuron (RFN) model, and then consider noise effects on its performance of signal detection. The suitable to have a deterministic approach to predict the second-order membrane dynamics and exhibits dynamic behavior, such as fast subthreshold oscillation, approach to improve the robustness. This also leads to a higher yield, which is of primal importance in mass RFN circuit acts as a band-pass filter and a coincidence detector at circuit level. Through SPICE simulations, we will demonstrate noise effects on the coincidence detection and the frequency preference of the RFN circuit