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Networks of Coupled VO2 Oscillators for Neuromorphic Computing

Publications associées (89)

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Time-Delay Encoded Image Recognition in a Network of Resistively Coupled VO2 on Si Oscillators

Kirsten Emilie Moselund, Siegfried Karg

Oscillatory neural networks based on insulator to metal transition of VO2 switches are implemented for image recognition. The VO2 oscillators are fabricated on silicon in a CMOS compatible process.A fullyconnected network of coupled oscillators is investig ...

2020

Local Vulnerabilities and Global Robustness of Coupled Dynamical Systems on Complex Networks

Melvyn Sandy Tyloo

Coupled dynamical systems are omnipresent in everyday life. In general, interactions between individual elements composing the system are captured by complex networks. The latter greatly impact the way coupled systems are functioning and evolving in time. ...

EPFL2020

Deep learning-based BCI for gait decoding from EEG with LSTM recurrent neural network

Silvestro Micera, Fiorenzo Artoni, Stefano Tortora

Objective.Mobile Brain/Body Imaging (MoBI) frameworks allowed the research community to find evidence of cortical involvement at walking initiation and during locomotion. However, the decoding of gait patterns from brain signals remains an open challenge. ...

IOP PUBLISHING LTD2020

Multi-memristive synaptic architectures for training neural networks

Irem Boybat Kara

Highly data-centric AI workloads require that new computing paradigms be adopted because the performance of traditional CPU- and GPU-based systems are limited by data access and transfer. Training deep neural networks with millions of tunable parameters ta ...

EPFL2020

Unified Neural Encoding of BTFs

Wenzel Alban Jakob

Realistic rendering using discrete reflectance measurements is challenging, because arbitrary directions on the light and view hemispheres are queried at render time, incurring large memory requirements and the need for interpolation. This explains the des ...

WILEY2020

OrthoNet: Multilayer Network Data Clustering

Pascal Frossard, Mireille El Gheche, Giovanni Chierchia

Network data appears in very diverse applications, like biological, social, or sensor networks. Clustering of network nodes into categories or communities has thus become a very common task in machine learning and data mining. Network data comes with some ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

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We present a new mechanical oscillator architecture that can be made insensitive to linear and angular accelerations while keeping constant oscillation frequency. The oscillator has the kinematics of a Watt linkage, so we call it a Watt oscillator. In orde ...

EUSPEN2020

A Nitride Ring Isolator

Tobias Kippenberg, Anat Siddharth, Junqiu Liu

A silicon nitride optical ring isolator is realized by spatiotemporal modulation using bulk acoustic wave stress-optical transducers. By driving three actuators with fixed relative phases, over 17 dB isolation is achieved. (C) 2020 The Author(s) ...

IEEE2020

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New computation schemes inspired by biological processes can outperform standard von-Neumann architectures in dealing with complex and unstructured tasks. As a new approach, systems of frequency-locked, coupled oscillators are investigated using the phase ...

IEEE2019

How single neuron properties shape chaotic dynamics and signal transmission in random neural networks

Wulfram Gerstner, Tilo Schwalger, Samuel Pavio Muscinelli

While most models of randomly connected neural networks assume single-neuron models with simple dynamics, neurons in the brain exhibit complex intrinsic dynamics over multiple timescales. We analyze how the dynamical properties of single neurons and recurr ...

2019