98 citations · 110 across the 5 of their papers we have counts for
7 papers
An Open-Source Standard-Cell Library for IHP 130nm Developed by Students
Oscar Castañeda, Lavinia Recchioni, Tobias Senti +26
Standard-cell libraries form the critical interface between transistor-level circuit design and automated digital design flows, yet their design and characterization are rarely cov…
TEXEL: A neuromorphic processor with on-chip learning for beyond-CMOS device integration
Hugh Greatorex, Ole Richter, Michele Mastella +10
Recent advances in memory technologies, devices and materials have shown great potential for integration into neuromorphic electronic systems. However, a significant gap remains be…
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…
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…
Spike-based local synaptic plasticity: A survey of computational models and neuromorphic circuits
Lyes Khacef, Philipp Klein, Matteo Cartiglia +3
Understanding how biological neural networks carry out learning using spike-based local plasticity mechanisms can lead to the development of powerful, energy-efficient, and adaptiv…
Stochastic dendrites enable online learning in mixed-signal neuromorphic processing systems
Matteo Cartiglia, Arianna Rubino, Shyam Narayanan +4
The stringent memory and power constraints required in edge-computing sensory-processing applications have made event-driven neuromorphic systems a promising technology. On-chip on…
Ultra-Low-Power FDSOI Neural Circuits for Extreme-Edge Neuromorphic Intelligence
Arianna Rubino, Can Livanelioglu, Ning Qiao +2
Recent years have seen an increasing interest in the development of artificial intelligence circuits and systems for edge computing applications. In-memory computing mixed-signal n…