A Spiking Neural Network with a Global Self-Controller for Unsupervised Learning Based on Spike-Timing-Dependent Plasticity Using Flash Memory Synaptic Devices.
Won-Mook KangChul-Heung KimSoochang LeeSung Yun WooJong-Ho BaeByung-Gook ParkJong-Ho LeePublished in: IJCNN (2019)
Keyphrases
- spiking neural networks
- unsupervised learning
- flash memory
- biologically inspired
- feed forward
- liquid state machine
- hand held devices
- embedded systems
- learning rules
- synaptic plasticity
- biologically plausible
- spiking neurons
- artificial neural networks
- neural network
- hebbian learning
- cerebellar model
- storage devices
- main memory
- solid state
- file system
- supervised learning
- control system
- semi supervised
- motor control
- dimensionality reduction
- neuron model
- b tree
- closed loop
- training algorithm
- mobile devices
- machine learning
- network architecture
- random access
- data storage
- personal computer
- low cost
- back propagation
- management system
- multi dimensional
- control scheme
- high dimensional
- feature space
- control strategy
- object recognition
- real time