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Detection Under One-Bit Messaging Over Adaptive Networks

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Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions

Andreas Loukas, Nikolaos Karalias

Integrating functions on discrete domains into neural networks is key to developing their capability to reason about discrete objects. But, discrete domains are (I) not naturally amenable to gradient-based optimization, and (II) incompatible with deep lear ...

2022

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Fourier transforms are an often necessary component in many computational tasks, and can be computed efficiently through the fast Fourier transform (FFT) algorithm. However, many applications involve an underlying continuous signal, and a more natural choi ...

2022

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A method for performing synchrophasor estimation of an input signal , whereby the input signal is a sinusoidal power system voltage or current signal , comprising: a. Periodic ampling of a continuous time - domain waveform, consisting of a power system vol ...

2021

Dynamics of optical forces and torques in plasmonic systems: a surface integral equation

Olivier Martin, Karim Achouri, Andrei Kiselev

A novel approach is introduced to determine the time evolution of optical forces and torques on arbitrary shape nanostructures by combining Maxwell's stress tensor with the surface integral equation method (SIE). Conventional time averaging of Maxwell’s st ...

SPIEDigitalLibrary2020

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We demonstrate sub-nanosecond wavelength switching, using a chip-based soliton microcomb and a semiconductor optical amplifier-based wavelength selector. 50-Gbps PAM4 transmission is achieved with discrete components and 25-Gbps NRZ with a photonic integra ...

IEEE2020

All in Good Time: Long-lasting Postdictive Effects Discrete Perception

Michael Herzog, Adrien Christophe Doerig, Leila Drissi Daoudi - Kleinbauer

Is consciousness a continuous stream of percepts or is it discrete, occurring only at certain moments in time? This question has puzzled philosophers, psychologists, and neuroscientists for centuries. Both hypotheses have fallen repeatedly in and out of fa ...

2020

Efficiently Learning Fourier Sparse Set Functions

Andreas Krause, Mikhail Kapralov, Amir Zandieh

Learning set functions is a key challenge arising in many domains, ranging from sketching graphs to black-box optimization with discrete parameters. In this paper we consider the problem of efficiently learning set functions that are defined over a ground ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2019

Calculus of variations: A differential form approach

Swarnendu Sil

We study integrals of the form integral(Omega) f(d omega(1), ..., d omega(m)), where m >= 1 is a given integer, 1

WALTER DE GRUYTER GMBH2019

A Fourier-accelerated volume integral method for elastoplastic contact

Jean-François Molinari, Guillaume Anciaux, Lucas Henri Galilée Frérot

The contact of solids with rough surfaces plays a fundamental role in physical phenomena such as friction, wear, sealing, and thermal transfer. However, its simulation is a challenging problem due to surface asperities covering a wide range of length-scale ...

2019

Reconstructing continuous signals based on a small number of discrete samples is a fundamental problem across science and engineering. We are often interested in signals with "simple" Fourier structure - e.g., those involving frequencies within a bounded r ...

ASSOC COMPUTING MACHINERY2019