A neuromorphic system is composed of hardware-based artificial neurons and synaptic
devices, designed to improve the efficiency of neural computations inspired by energy …

In the vanguard of neuromorphic engineering, we develop a paradigm of biocompatible
polymer memcapacitors using a seamless solution process, unleashing comprehensive …

Advancements in neuromorphic computing have given an impetus to the development of
systems with adaptive behavior, dynamic responses, and energy efficiency characteristics …

The development of neuromorphic systems necessitates the use of memcapacitors that can
adapt to optoelectronic modulation. Two-dimensional (2D) materials with atomically thin …

There is a need to design a hardware synapse array appropriate for enhancing the
efficiency of neuromorphic computing systems while minimizing energy consumption. This …

Most associative memory neural networks are realized by memristor, but memcapacitor
which can simulate the biological behavior of neuron preferably has better characteristics …

A flash memory is a non-volatile memory that has a large memory window, high cell density,
and reliable switching characteristics and can be used as a synaptic device in a …

This paper addresses critical gaps in the digital implementations of fractional-order
memelement emulators, particularly given the challenges associated with the development …

To mimic the homeostatic functionality of biological neurons, a split-gate field-effect
transistor (SG FET) with a charge trap layer is proposed within a neuron circuit. By adjusting …

In this article, we propose a coupling-free readout scheme designed for a hardware neural
network employing memcapacitive devices based on Si MOS capacitors having a charging …