A Spiking Recurrent Neural Network With Phase-Change Memory Neurons and Synapses for the Accelerated Solution of Constraint Satisfaction Problems

A Spiking Recurrent Neural Network With Phase-Change Memory Neurons and Synapses for the Accelerated Solution of Constraint Satisfaction Problems

Data-intensive computing applications, such as object recognition, time series prediction, and optimization tasks, are becoming increasingly important in several fields, including smart mobility, health, and industry. Because of the large amount of data involved in the computation, the conventional...

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Bibliographic Details
Main Authors: Giacomo Pedretti, Piergiulio Mannocci, Shahin Hashemkhani, Valerio Milo, Octavian Melnic, Elisabetta Chicca, Daniele Ielmini
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Subjects:
Phase change memory (PCM)
artificial synapses
hopfield neural network
stochastic process
optimization
Online Access:https://ieeexplore.ieee.org/document/9086758/

Internet

https://ieeexplore.ieee.org/document/9086758/

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