Academic Articles & Research Papers

Benchmarking spiking neurons for linear quadratic regulator control of multi-linked pole on a cart: from single neuron to ensemble

The emerging field of neuromorphic computing for edge control applications poses the need to quantitatively estimate and limit the number of spiking neurons, to reduce network complexity and optimize the number of neurons per core and hence...

From Nano Robotic Manipulation to Nano Manipulation Robot

ABSTRACT The evolution from passive nanoscale observation to active robotic manipulation represents a paradigm shift in humanity's quest to master matter at the atomic scale. This review systematically traces the historical and conceptual f...

Robust Resistive Switching Constancy and Quantum Conductance in High-k Dielectric-Based Memristor for Neuromorphic Engineering

Abstract For neuromorphic computing and high-density data storage memory, memristive devices have recently gained a lot of interest. So far, memristive devices have suffered from switching parameter instability, such as distortions in resis...

CsPbBr3/graphene nanowall artificial optoelectronic synapses for controllable perceptual learning

Abstract The rapid development of neuromorphic computing has stimulated extensive research interest in artificial synapses. Optoelectronic artificial synapses using laser beams as stimulus signals have the advantages of broadband, fast resp...

Canonical quantization of a memristive leaky integrate-and-fire neuron circuit

We present a theoretical framework for a quantized memristive Leaky Integrate-and-Fire (LIF) neuron, uniting principles from neuromorphic engineering and open quantum systems. Starting from a classical memristive LIF circuit, we apply canon...

Modeling of Self-Aligned Selector Based on Ultra-Thin Metal Oxide for Resistive Random-Access Memory (RRAM) Crossbar Arrays

Resistive random-access memory (RRAM) is a crucial element for next-generation large-scale memory arrays, analogue neuromorphic computing and energy-efficient System-on-Chip applications. For these applications, RRAM elements are arranged i...

Memristor Synapse—A Device-Level Critical Review

The memristor has long been known as a nonvolatile memory technology alternative and has recently been explored for neuromorphic computing, owing to its capability to mimic the synaptic plasticity of the human brain. The architecture of a m...

Neuromorphic Computing Using Synaptic Plasticity of Supercapacitors

Abstract Neuromorphic computing systems convert multimodal signals to electrical responses for artificial intelligence recognition. Energy is consumed during both the response enhancement and depression, making the systems suffer from high ...

Photonics for artificial intelligence and neuromorphic computing