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A phase-change memory model for neuromorphic computing

Related publications (34)

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2D Nanosystems: Applications of 2D Semiconductors for In-Memory Computing

Guilherme Migliato Marega

Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today's ...

EPFL2023

We consider high-dimensional random optimization problems where the dynamical variables are subjected to nonconvex excluded volume constraints. We focus on the case in which the cost function is a simple quadratic cost and the excluded volume constraints a ...

AMER PHYSICAL SOC2022

A dynamical systems approach to synaptic consolidation and associations of concepts in hippocampus

Chiara Gastaldi

In the present work, we approach two key aspects of memory formation: associative memory and synaptic consolidation. The storage of associative memory is commonly related to the medial temporal lobe in humans. Experimental evidence shows that the memories ...

EPFL2021

Networks of Coupled VO2 Oscillators for Neuromorphic Computing

Elisabetta Corti

Neuromorphic computing is a wide research field aimed to the realization of brain-inspired hardware, apt to tackle computation of unstructured data more efficiently than currently done with standard computational units. Oscillatory neural networks are know ...

EPFL2021

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A random access memory having a memory array having a plurality of local memory groups, each local memory group including a plurality of bitcells arranged in a bitcell column, a pair of local bitlines operatively connected to the plurality of bitcells, a p ...

2021

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A detailed synchrotron X-ray diffraction (XRD) study performed with a single crystal of BaVS3 (barium vanadium trisulfide) in the temperature range between 10 and 295 K is reported. Aside from the known tetragonal–orthorhombic (240 K) and orthorhombic–mono ...

2021

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Resistive switching memory technologies (RRAM) are seen by most of the scientific community as an enabler for Edge-level applications such as embedded deep Learning, AI or signal processing of audio and video signals. However, going beyond a "simple'' repl ...

IEEE2020

Experimental Demonstration of Supervised Learning in Spiking Neural Networks with Phase-Change Memory Synapses

Irem Boybat Kara, Evangelos Eleftheriou, Abu Sebastian

Spiking neural networks (SNN) are computational models inspired by the brain's ability to naturally encode and process information in the time domain. The added temporal dimension is believed to render them more computationally efficient than the conventio ...

2020

Melting of a skyrmion lattice to a skyrmion liquid via a hexatic phase

Henrik Moodysson Rønnow, Arnaud Magrez, Marco Cantoni, Fabrizio Carbone, Ping Huang, Thomas Schönenberger

While in 3D materials melting is a single, first-order phase transition, in 2D systems, it can also proceed via an intermediate phase. For a skyrmion lattice in Cu2OSeO3, magnetic field variations can tune this quasiparticle 2D solid into a skyrmion liquid ...

NATURE PUBLISHING GROUP2020

STEERABLE CATHETER WITH PORTIONS OF DIFFERENT STIFFNESS

Dario Floreano, Alice Tonazzini

A steerable catheter (10) comprises portions (100, 105) of different stiffness, having a proximal end (11), a distal end, a lumen extending there between, at least one magnet (20) at the proximal end (11), at least a magnetic field to influence the proxima ...

2019