Resistive switching materials for information processing
The rapid increase in information in the big-data era calls for changes to information-
processing paradigms, which, in turn, demand new circuit-building blocks to overcome the …
processing paradigms, which, in turn, demand new circuit-building blocks to overcome the …
Nanostructured perovskites for nonvolatile memory devices
Q Liu, S Gao, L Xu, W Yue, C Zhang, H Kan… - Chemical Society …, 2022 - pubs.rsc.org
Perovskite materials have driven tremendous advances in constructing electronic devices
owing to their low cost, facile synthesis, outstanding electric and optoelectronic properties …
owing to their low cost, facile synthesis, outstanding electric and optoelectronic properties …
In-sensor reservoir computing system for latent fingerprint recognition with deep ultraviolet photo-synapses and memristor array
Detection and recognition of latent fingerprints play crucial roles in identification and
security. However, the separation of sensor, memory, and processor in conventional ex-situ …
security. However, the separation of sensor, memory, and processor in conventional ex-situ …
In materia reservoir computing with a fully memristive architecture based on self-organizing nanowire networks
Neuromorphic computing aims at the realization of intelligent systems able to process
information similarly to our brain. Brain-inspired computing paradigms have been …
information similarly to our brain. Brain-inspired computing paradigms have been …
Experimental demonstration of highly reliable dynamic memristor for artificial neuron and neuromorphic computing
Neuromorphic computing, a computing paradigm inspired by the human brain, enables
energy-efficient and fast artificial neural networks. To process information, neuromorphic …
energy-efficient and fast artificial neural networks. To process information, neuromorphic …
Dynamic memristor-based reservoir computing for high-efficiency temporal signal processing
Reservoir computing is a highly efficient network for processing temporal signals due to its
low training cost compared to standard recurrent neural networks, and generating rich …
low training cost compared to standard recurrent neural networks, and generating rich …
In-sensor reservoir computing for language learning via two-dimensional memristors
The dynamic processing of optoelectronic signals carrying temporal and sequential
information is critical to various machine learning applications including language …
information is critical to various machine learning applications including language …
Emerging memristive artificial synapses and neurons for energy‐efficient neuromorphic computing
Memristors have recently attracted significant interest due to their applicability as promising
building blocks of neuromorphic computing and electronic systems. The dynamic …
building blocks of neuromorphic computing and electronic systems. The dynamic …
Physical reservoir computing—an introductory perspective
K Nakajima - Japanese Journal of Applied Physics, 2020 - iopscience.iop.org
Understanding the fundamental relationships between physics and its information-
processing capability has been an active research topic for many years. Physical reservoir …
processing capability has been an active research topic for many years. Physical reservoir …
Multilayer Reservoir Computing Based on Ferroelectric α‐In2Se3 for Hierarchical Information Processing
Dynamic physical systems such as reservoir computing (RC) architectures show a great
prospect in temporal information processing, whereas hierarchical information processing …
prospect in temporal information processing, whereas hierarchical information processing …