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We extend the concept of self-consistency for the Fokker-Planck equation (FPE) [Shen et al., 2022] to the more general McKean-Vlasov equation (MVE). While FPE describes the macroscopic behavior of par...
Deep neural networks, as a powerful system to represent high dimensional complex functions, play a key role in deep learning. Convergence of deep neural networks is a fundamental issue in building the...
Abstract: We present an analysis of the Locally Competitive Algorithm (LCA), a Hopfield-style neural network that solves sparse approximation problems (e.g., approximating a vector from a dictionary u...
This paper contains novel model using feedback neural networks for a work piece temperature predic- tion.The heat and mass transfer in a porous metal workpiece which is heated by a fire gun is studied...
The novel approach to the extraction of the two-photon exchange (TPE) correction from the elastic $ep$ scattering data is presented. The Bayesian framework for the neural networks is adapted. As the r...
In this paper, the model of stochastic fuzzy Hopfield neural networks with time-varying delays and impulses (ISFVDHNNs) is established as a modified Takagi-Sugeno (TS) fuzzy model in which the consequ...
A wavelet network is an important tool for analyzing time series especially when it is nonlinear and non-stationary. It takes advantage of high resolution of wavelets and learning and feed forward nat...
We study the dynamics of two symmetrically coupled populations of leaky integrate-and-fire neurons characterized by an excitatory coupling. Upon varying the coupling strength, we find symmetry-breakin...
We study the global dynamics of integrate and fire neural networks composed of an arbitrary number of identical neurons interacting by inhibition and excitation. We prove that if the interactions are...
In this paper we propose an investing strategy based on neural network models combined with ideas from game-theoretic probability of Shafer and Vovk. Our proposed strategy uses parameter values of a n...
A large number of approaches for texture analysis have been suggested for the purpose of texture classification. Recently, wavelet frames were proposed for texture features extraction. In this study, ...
In this paper, a discrete-time bidirectional associative memory (BAM) neural network with time-varying delays is considered. The description of the activation functions is more general than the recent...
In this paper, the impulsive fuzzy recurrent neural network with both time-varying delays and distributed delays is considered. Applying the idea of vector Lyapunov function, M-matrix theory and analy...
Computational models made up of linear combinations of ridge basis functions, widely used in machine learning and artificial intelligence, are considered. For such models, the literature on the so-cal...
Based on the recent result given in Park [19], a further result for global asymptotic stability of the equilibrium point for a class of uncertain neural networks with discrete and distributed delays i...

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