Semiconductor Memory Devices for Hardware-Driven Neuromorphic Systems

Semiconductor Memory Devices for Hardware-Driven Neuromorphic Systems

This book aims to convey the most recent progress in hardware-driven neuromorphic systems based on semiconductor memory technologies. Machine learning systems and various types of artificial neural networks to realize the learning process have mainly focused on software technologies. Tremendous adva...

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Bibliographic Details
Other Authors: Cho, Seongjae (Editor)
Format: Book Chapter
Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Subjects:
Technology: general issues
Energy industries & utilities
leaky integrate-and-fire neuron
vanadium dioxide
neural network
pattern recognition
a-IGZO memristor
Schottky barrier tunneling
non filamentary resistive switching
gradual and abrupt modulation
bimodal distribution of effective Schottky barrier height
ionized oxygen vacancy
energy consumption
hardware-based neuromorphic system
synaptic device
Si processing compatibility
TCAD device simulation
benchmarking neuromorphic HW
neuromorphic platform
spiNNaker
spinMPI
MPI for neuromorphic HW
Boyer-Moore
DNA matching algorithm
flexible electronics
neuromorphic engineering
organic field-effect transistors
synaptic devices
short-term plasticity
neuromorphic system
on-chip learning
overlapping pattern issue
spiking neural network
3-D neuromorphic system
3-D stacked synapse array
charge-trap flash synapse
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