Subthreshold Modeling of a Tunable CMOS Schmitt Trigger

Abstract

In this article, the subthreshold characteristics of a tunable single input CMOS Schmitt trigger (ST) are modeled for the first time. The high-to-low and low-to-high hysteresis transition points are analytically determined as a function of the tuning voltages and the transistors' geometrical parameters. The derived expressions allow to design the ST with desired hysteresis width in subthreshold region. Furthermore, the proposed model allows to estimate the minimum supply voltage for which hysteresis occurs. The derived expressions also provide physical insight into the circuit behavior, by predicting the effect of supply voltage and temperature variations on the hysteresis width. The model is validated through simulations, and the maximum error between the analytical and simulated transition points is less than 5%. The model is also experimentally validated with an ASIC fabricated in AMS 0.35µm CMOS process. The maximum error between the analytical and measured transition points is below 6%. The analytical model allows performance optimization in subthreshold region for low power applications.INDEX TERMS CMOS, hysteresis, low voltage, Schmitt trigger, subthreshold.

Biologically Inspired Tonic and Bursting LIF Neuron Model for Spiking Neural Network: A CMOS Implementation

“…For storage-oriented applications, a broader hysteresis width is advantageous, whereas switching-oriented applications require a narrower width. The design of the LIF neuron takes place a smaller-width hysteresis to trigger spikes upon reaching the switching threshold, thereby minimizing power consumption [27], [28]. The transistors' size and power consumption details are summarized in Table 1.…”

“…The standard criteria, such as average power consumption, hysteresis voltage, and noise margin levels of this low-power CMOS Schmitt trigger, are compared against conventional static CMOS-based Schmitt trigger to ensure the suitability of the proposed biological silicon LIF neuron model. The analysis reveals that this particular CMOS Schmitt trigger exhibits lower power consumption due to the low resistance path of discharge [27], [28]. Moreover, it offers generous hysteresis and noise margin thresholds, rendering it a preferred choice for the proposed LIF neuron model in a noise environment.…”