Results 141 to 150 of about 3,666 (171)

Ocean transit times: from basin to planetary scales. [PDF]

J Fluid Mech
Cessi P.
europepmc   +1 more source

Model-agnostic linear-memory online learning in spiking neural networks. [PDF]

Nat Commun
Wang C, Dong X, Ji Z, Xiao M, Jiang J, Liu X, Huan Y, Wu S.   +7 more
europepmc   +1 more source

Event-Driven Spiking Neural Networks for Private Vehicle Parking Prediction. [PDF]

Entropy (Basel)
Long W, Chen J.
europepmc   +1 more source

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Recursive Heaviside step functions and beginning of the universe

New Astronomy, 2017
Abstract This article introduces recursive Heaviside step functions, as a potential of the known universe, for the first time in the history of mathematics, science, and engineering. In modern cosmology, various bouncing models have been suggested based on the postulation that the current universe is the result of the collapse of a previous universe.
Changsoo Shin, Seongjai Kim
exaly   +2 more sources

Excitation of medium by Heaviside step function of electric field

2016 10th European Conference on Antennas and Propagation (EuCAP), 2016
An analytical solution in a closed form to the problem of excitation of a medium by Heaviside step function of electric field has been obtained. It allows for studying fields excited by impulse (non-smooth) sources. Numerical results of fields' calculation in a medium are presented.
V. I. Naydenko, D. S. Shumakov
exaly   +2 more sources

On the Hausdorff distance between the Heaviside step function and Verhulst logistic function

Journal of Mathematical Chemistry, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Svetoslav Markov, Nikolay Kyurkchiev, Markov Svetoslav   +2 more
exaly   +3 more sources

Derivative of Heaviside step function vs. delta function in continuum surface force (CSF) models

International Journal of Multiphase Flow, 2018
Abstract In Continuum Surface Force (CSF) model for implementing surface tension forces in multiphase flows, singular delta function is used to merge two continuous sets of flow equations. Discretizing the delta function has attracted a great deal of attention and has led to developing many different approaches. It has been shown numerically that two
Hanif Montazeri, Seyed Hadi Zandavi
exaly   +2 more sources

Analysis and Design of a $k$-Winners-Take-All Model With a Single State Variable and the Heaviside Step Activation Function

IEEE Transactions on Neural Networks, 2010
This paper presents a k-winners-take-all (kWTA) neural network with a single state variable and a hard-limiting activation function. First, following several kWTA problem formulations, related existing kWTA networks are reviewed. Then, the kWTA model model with a single state variable and a Heaviside step activation function is described and its global
Jun Wang
exaly   +3 more sources