An Area- and Energy-Efficient Spiking Neural Network With Spike-Time-Dependent Plasticity Realized With SRAM Processing-in-Memory Macro and On-Chip Unsupervised Learning.
Shuang LiuJunjie WangJingtao ZhouShaogang HuQi YuTupei ChenYang LiuPublished in: IEEE Trans. Biomed. Circuits Syst. (2023)
Keyphrases
- energy efficient
- spiking neural networks
- unsupervised learning
- spiking neurons
- random access memory
- biologically inspired
- wireless sensor networks
- energy consumption
- data transmission
- sensor networks
- power consumption
- biologically plausible
- energy efficiency
- learning rules
- feed forward
- base station
- supervised learning
- power dissipation
- real time
- data processing
- memory access
- memory management
- dynamic random access memory
- cerebellar model
- motor control
- low cost
- artificial neural networks
- object recognition
- routing protocol
- main memory
- sensor nodes
- data acquisition
- embedded dram
- memory subsystem
- high speed
- routing algorithm
- memory bandwidth
- spike trains
- cmos technology
- dimensionality reduction
- learning algorithm
- machine learning
- neural network