The motivation for driving semiconductor devices can be found in the development of
advanced computers which can contribute to the betterment in our daily lives. The …

This article aims to study fixed-time projective lag synchronization (FXPLS) and preassigned-
time projective lag synchronization (PTPLS) of hybrid inertial neural networks (HINNs) with …

In this work, a synaptic device for neuromorphic system is proposed and designed to
emulate the biological behaviors in the novel device structure of core-shell dual-gate …

The artificial neural networks based on biomimetic synaptic devices attempts to process and
memorize information by simulating a human brain. Electrolyte-gated transistors (EGTs) are …

Brain-inspired structured neural circuits are the cornerstones of both computational and
perceived intelligence. Real-time simulations of large-scale high-dimensional neural …

In this work, a synaptic weight transfer method for a neuromorphic system based on resistive-
switching random-access memory (RRAM) is proposed and validated. To implement the on …

In this article, a synaptic semiconductor device and its crossbar have been demonstrated for
real-time artificial intelligence (AI) applications. The proposed device is a dual gate, metal …

For the development of brain-inspired neuromorphic hardware with high integration density
and connectivity in this work, we have proposed a fully planar, CMOS compatible, and …

Despite their great synaptic potential, the trade-off between programming speed and energy
consumption of electrochemical random-access memory (ECRAM) devices are major …

Integrate-and-fire (IAF) and leaky integrate-and-fire (LIF) models are the popular models for
spiking neurons and spiking neuron networks (SNN). They lack the dynamic properties of …