All‐Solid‐State Synaptic Transistor with Ultralow Conductance for Neuromorphic Computing

Novel synaptic memory device for neuromorphic computing

This report discusses the electrical characteristics of two-terminal synaptic memory devices capable of demonstrating an analog change in conductance in response to the varying amplitude and pulse-width of the applied signal. The devices are based on Mn doped HfO₂ material. The mechanism behind reconfiguration was studied and a unified model is presented to explain the underlying device physics...

Stochastic learning in oxide binary synaptic device for neuromorphic computing

Hardware implementation of neuromorphic computing is attractive as a computing paradigm beyond the conventional digital computing. In this work, we show that the SET (off-to-on) transition of metal oxide resistive switching memory becomes probabilistic under a weak programming condition. The switching variability of the binary synaptic device implements a stochastic learning rule. Such stochast...

Optimization of Conductance Change in Pr1−xCaxMnO3-Based Synaptic Devices for Neuromorphic Systems

The optimization of conductance change behavior in synaptic devices based on analog resistive memory is studied for the use in neuromorphic systems. Resistive memory based on Pr1−xCaxMnO3 (PCMO) is applied to a neural network application (classification of Modified National Institute of Standards and Technology handwritten digits using a multilayer perceptron trained with backpropagation) under...

Editorial: Synaptic Plasticity for Neuromorphic Systems

Brain plasticity serves animals in a wide range of vital functions. It assists them in adapting their behavior to the surroundings, in learning new strategies for optimizing a certain reward-seeking policy for their survival or in adjusting motor activity through sensory feedback. Thus, plasticity is an essential ingredient for building artificial autonomous systems that can cope with the real ...

Tutorial: Neuromorphic computing