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SPAIC: A sub-$μ$W/Channel, 16-Channel General-Purpose Event-Based Analog Front-End with Dual-Mode Encoders
Low-power event-based analog front-ends (AFE) are a crucial component required to build efficient end-to-end neuromorphic processing systems for edge computing.
Neuromorphic analog circuits for robust on-chip always-on learning in spiking neural networks
We designed a spiking neural network with these learning circuits in a prototype chip using a 180 nm CMOS technology.
Spike-based local synaptic plasticity: A survey of computational models and neuromorphic circuits
To this end, in this survey, we provide a comprehensive overview of representative brain-inspired synaptic plasticity models and mixed-signal CMOS neuromorphic circuits within a unified framework.
Online Detection of Vibration Anomalies Using Balanced Spiking Neural Networks
Vibration patterns yield valuable information about the health state of a running machine, which is commonly exploited in predictive maintenance tasks for large industrial systems.
An error-propagation spiking neural network compatible with neuromorphic processors
Spiking neural networks have shown great promise for the design of low-power sensory-processing and edge-computing hardware platforms.
