1.1k citations · 4.6k across the 68 of their papers we have counts for
74 papers
Feed-forward and recurrent inhibition for compressing and classifying high dynamic range biosignals in spiking neural network architectures
Rachel Sava, Elisa Donati, Giacomo Indiveri
Neuromorphic processors that implement Spiking Neural Networks (SNNs) using mixed-signal analog/digital circuits represent a promising technology for closed-loop real-time processi…
SPAIC: A sub-W/Channel, 16-Channel General-Purpose Event-Based Analog Front-End with Dual-Mode Encoders
Shyam Narayanan, Matteo Cartiglia, Arianna Rubino +3
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. Although several ne…
Yak: An Asynchronous Bundled Data Pipeline Description Language
Carsten Nielsen, Zhe Su, Giacomo Indiveri
The design of asynchronous circuits typically requires a judicious definition of signals and modules, combined with a proper specification of their timing constraints, which can be…
Core interface optimization for multi-core neuromorphic processors
Zhe Su, Hyunjung Hwang, Tristan Torchet +1
Hardware implementations of Spiking Neural Networks (SNNs) represent a promising approach to edge-computing for applications that require low-power and low-latency, and which canno…
Neuromorphic analog circuits for robust on-chip always-on learning in spiking neural networks
Arianna Rubino, Matteo Cartiglia, Melika Payvand +1
Mixed-signal neuromorphic systems represent a promising solution for solving extreme-edge computing tasks without relying on external computing resources. Their spiking neural netw…
Scaling Limits of Memristor-Based Routers for Asynchronous Neuromorphic Systems
Junren Chen, Siyao Yang, Huaqiang Wu +2
Multi-core neuromorphic systems typically use on-chip routers to transmit spikes among cores. These routers require significant memory resources and consume a large part of the ove…