The rapid development of information technology has led to urgent requirements for high
efficiency and ultralow power consumption. In the past few decades, neuromorphic …

To process data operations more efficiently in deep neural networks (DNNs), studies on
spiking neural networks (SNNs) have been conducted. In the reported literature, CMOS …

Artificial neurons have received extensive attention as an important part of neuromorphic
computing. Recently, tremendous efforts have been made on the memristor-based neurons …

There have been recent efforts towards the development of biologically-inspired
neuromorphic devices and architecture. Here, we show a synapse circuit that is designed to …

With high efficiency and low energy consumption, bio-inspired artificial neuromorphic
systems are regarded as the next generation of computing methods and have attracted …

Artificial neurons have good application prospects as efficient processing units in artificial
neural morphology. Indiun galliun zinc oxide (IGZO) is widely used in artificial synapses and …

We have developed a capacitor-less I&F neuron circuit with a dual gate positive feedback
fieldeffect transistor (FBFET) and successfully co-integrated FBFET and CMOS in a wafer. By …

The stochastic neuron is a key for event-based probabilistic neural networks. We propose a
stochastic neuron using a metal-oxide resistive random-access memory (ReRAM). The …

In this paper, we present an input-modulating adaptive neuron circuit employing a floating-
gate MOSFET (FG-MOSFET) with two asymmetrically shaped control gates. The proposed …

The most important aspect of an artificial neuron circuit is energy consumption. An analog
neuron circuit has a critical problem in that the energy consumption in the steady-state due …