Search Results for author: Arianna Rubino

Found 4 papers, 0 papers with code

SPAIC: A sub-$μ$W/Channel, 16-Channel General-Purpose Event-Based Analog Front-End with Dual-Mode Encoders

no code implementations31 Aug 2023 Shyam Narayanan, Matteo Cartiglia, Arianna Rubino, Charles Lego, Charlotte Frenkel, Giacomo Indiveri

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.

Edge-computing

Neuromorphic analog circuits for robust on-chip always-on learning in spiking neural networks

no code implementations12 Jul 2023 Arianna Rubino, Matteo Cartiglia, Melika Payvand, Giacomo Indiveri

We designed a spiking neural network with these learning circuits in a prototype chip using a 180 nm CMOS technology.

Edge-computing

Spike-based local synaptic plasticity: A survey of computational models and neuromorphic circuits

no code implementations30 Sep 2022 Lyes Khacef, Philipp Klein, Matteo Cartiglia, Arianna Rubino, Giacomo Indiveri, Elisabetta Chicca

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.

Ultra-Low-Power FDSOI Neural Circuits for Extreme-Edge Neuromorphic Intelligence

no code implementations25 Jun 2020 Arianna Rubino, Can Livanelioglu, Ning Qiao, Melika Payvand, Giacomo Indiveri

Recent years have seen an increasing interest in the development of artificial intelligence circuits and systems for edge computing applications.

Edge-computing

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