Results 21 to 30 of about 4,172,567 (219)
Fixed-Time Synchronization of Delayed Memristive Neural Networks with Discontinuous Activations
Journal of Mathematics, 2021 In this paper, the fixed-time synchronization problem for a class of memristive neural networks with discontinuous neuron activation functions and mixed time-varying delays is investigated.
Hao Pu, Fengjun Li
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ayrna/deep-activation-functions: Paper IJCNN 2020
, 2020 Code of paper 'Are activation functions the cornerstone of deep learning?' submitted to IJCNN ...
Víctor Vargas
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Application of a Discontinuous Galerkin Method to Predict Airframe Noise [PDF]
, 2009 Unstructured grids greatly ease the mesh generation process in the case of complex geometries. The Discontinuous Galerkin Method (DGM) provides a robust, high-order accurate discretization even on this type of grid.
Marcus Bauer +5 more
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Robust generalized Mittag-Leffler synchronization of fractional order neural networks with discontinuous activation and impulses [PDF]
, 2018 Fractional order system is playing an increasingly important role in terms of both theory and applications. In this paper we investigate the global existence of Filippov solutions and the robust generalized Mittag-Leffler synchronization of fractional ...
Cao, Jinde +11 more
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A Neural Network Approximation Based on a Parametric Sigmoidal Function
Mathematics, 2019 It is well known that feed-forward neural networks can be used for approximation to functions based on an appropriate activation function. In this paper, employing a new sigmoidal function with a parameter for an activation function, we consider a ...
Beong In Yun
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An hp-version discontinuous Galerkin method for integro-differential equations of parabolic type [PDF]
, 2011 We study the numerical solution of a class of parabolic integro-differential equations with weakly singular kernels. We use an $hp$-version discontinuous Galerkin (DG) method for the discretization in time.
Brunner, Hermann +3 more
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On Shor's r-Algorithm for Problems with Constraints
Кібернетика та комп'ютерні технології, 2023 Introduction. Nonsmooth optimization problems arise in a wide range of applications, including engineering, finance, and deep learning, where activation functions often have discontinuous derivatives, such as ReLU.
Vladimir Norkin, Anton Kozyriev
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Abstract and Applied Analysis, 2013 The robust almost periodic dynamical behavior is investigated for interval neural networks with mixed time-varying delays and discontinuous activation functions.
Huaiqin Wu +4 more
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Energies, 2022 Physics-informed neural network (PINN) models are developed in this work for solving highly anisotropic diffusion equations. Compared to traditional numerical discretization schemes such as the finite volume method and finite element method, PINN models ...
Wenjuan Zhang, Mohammed Al Kobaisi
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Fluids, 2023 The study is dedicated to the peculiarities of implementing the flux limiter of the flow quantity gradient when solving 3D aerodynamic problems using the system of Navier–Stokes equations on unstructured meshes.
A. V. Struchkov +4 more
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