G
Giacomo Indiveri
Researcher at University of Zurich
Publications - 376
Citations - 15262
Giacomo Indiveri is an academic researcher from University of Zurich. The author has contributed to research in topics: Neuromorphic engineering & Spiking neural network. The author has an hindex of 47, co-authored 341 publications receiving 12201 citations. Previous affiliations of Giacomo Indiveri include Fraunhofer Society & Xi'an Jiaotong University.
Papers
More filters
Journal ArticleDOI
Neuromorphic Silicon Neuron Circuits
Giacomo Indiveri,Bernabe Linares-Barranco,Tara Julia Hamilton,André van Schaik,Ralph Etienne-Cummings,Tobi Delbruck,Shih-Chii Liu,Piotr Dudek,Philipp Hafliger,Sylvie Renaud,Johannes Schemmel,Gert Cauwenberghs,John V. Arthur,Kai Hynna,Fopefolu Folowosele,Sylvain Saïghi,Teresa Serrano-Gotarredona,Jayawan H B Wijekoon,Yingxue Wang,Kwabena Boahen +19 more
TL;DR: The most common building blocks and techniques used to implement these circuits, and an overview of a wide range of neuromorphic silicon neurons, which implement different computational models, ranging from biophysically realistic and conductance-based Hodgkin–Huxley models to bi-dimensional generalized adaptive integrate and fire models.
Journal ArticleDOI
A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity
TL;DR: In this article, a mixed-mode analog/digital VLSI device comprising an array of leaky integrate-and-fire (I&F) neurons, adaptive synapses with spike-timing dependent plasticity, and an asynchronous event based communication infrastructure is presented.
Journal ArticleDOI
A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses.
Ning Qiao,Hesham Mostafa,Federico Corradi,Marc Osswald,Fabio Stefanini,Dora Sumislawska,Giacomo Indiveri +6 more
TL;DR: This paper presents a full-custom mixed-signal VLSI device with neuromorphic learning circuits that emulate the biophysics of real spiking neurons and dynamic synapses for exploring the properties of computational neuroscience models and for building brain-inspired computing systems.
Journal ArticleDOI
Memory and Information Processing in Neuromorphic Systems
Giacomo Indiveri,Shih-Chii Liu +1 more
TL;DR: A survey of brain-inspired processor architectures that support models of cortical networks and deep neural networks is presented and the advantages and challenges that need to be addressed for building artificial neural processing systems that can display the richness of behaviors seen in biological systems are presented.
Journal ArticleDOI
Integration of nanoscale memristor synapses in neuromorphic computing architectures
Giacomo Indiveri,Bernabe Linares-Barranco,Robert Legenstein,George Deligeorgis,Themistoklis Prodromakis,Themistoklis Prodromakis +5 more
TL;DR: In this paper, a novel hybrid memristor-CMOS neuromorphic circuit is proposed, which represents a radical departure from conventional neuro-computing approaches, as it uses memristors to directly emulate the biophysics and temporal dynamics of real synapses.