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1 day ago · We invite you to delve into the top 10 cited papers in 2023 in the Section “Dynamical Systems” of the journal Mathematics (ISSN: 2227-7390). These papers, carefully selected for their exceptional quality and relevance, represent cutting-edge research in the Section “Dynamical Systems”. 1. “Dynamic Analysis and FPGA Implementation of a ...
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For instance, partial differential–difference equations...
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3 days ago · Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI. Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs).
3 days ago · For instance, partial differential–difference equations arise in the theory of multi-layer plates and envelopes (see [ 2, 6 ]), nonclassical diffusion theory including biomathematical applications (see [ 7, 8, 9 ]), and nonlinear optics (see [ 10, 11, 12, 13, 14, 15 ]).
5 days ago · We will study exponential convergence-(t, s)-weak tractability (EC-(t, s)-WT) for some t > 0, s > 0 and obtain the complete suficient and necessary conditions for t = s = 1 and t < 1, s = 1, respectively. The paper is structured in the following ways. We present three cases of weighted Hilbert spaces in Section 2.
5 days ago · Thus, the contributions of this study are as follows: (1) we explore two structure policies in an optimal solution to devise eficient algorithms to reduce computational complexity; (2) we provide a suficient condition for forecasting and decision horizons; and (3) we determine that, for a given fixed cost, the median forecast horizon first incre...
5 days ago · In mathematical random matrices theory for large rectangular random matrices, the Marchenko–Pastur measure describes the asymptotic behavior of the corresponding singular values.
5 days ago · A novel network structure combining Convolu-tional Neural Networks and Long Short-Term Memory Networks is designed to map the intersec-tion traffic state to a Q-value, accelerating the learning process. The reward mechanism involves a multi-objective optimization function, employing the entropy weight method to balance the weights among dual goals.
