Results 121 to 130 of about 45,363 (158)
DC Series Arc Fault Detection in Electric Vehicle Charging Systems Using a Temporal Convolution and Sparse Transformer Network. [PDF]
Sensors (Basel)Yang K +5 more
europepmc +1 more source
GroupCeptionNet: a lightweight model for classifying chili seed germination with macro images. [PDF]
Sci RepAo C, Xu T.
europepmc +1 more source
Data-driven global ocean model resolving atmospherically forced ocean dynamics. [PDF]
Sci AdvKim JH +4 more
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Convolution series and the generalized convolution Taylor formula [PDF]
Fractional Calculus and Applied Analysis, 2022 19 ...
Yuri Luchko, Luchko Yuri
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An Algorithm for the Convolution of Legendre Series [PDF]
SIAM Journal of Scientific Computing, 2014 An $\mathcal{O}(N^2)$ algorithm for the convolution of compactly supported Legendre series is described. The algorithm is derived from the convolution theorem for Legendre polynomials and the recurrence relation satisfied by spherical Bessel functions. Combining with previous work yields an $\mathcal{O}(N^2)$ algorithm for the convolution of Chebyshev ...
Nicholas Hale, Alex Townsend
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Some convolution series identities
Mathematical and Computer Modelling, 1995 A representation of a convolution series involving arbitrary sequences is obtained in terms of the derivatives of known generating functions. Another variation of the main result is given, and applications are shown to yield certain combinatorial identities and addition formulas.
R K Raina, H M Srivastava
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A Convolution Structure for Jacobi Series
American Journal of Mathematics, 1969Gangolli [6] discovered this convolution structure for special values of ac and J3 namely /3= 1/2, a = (n -1)/2; 3=0, ac n; and /3=1, a-2n + 1; 1 G= 3, c = 7. n here is a non-negative integer. Let P (a,0) (x) be the Jacobi polynomial of degree n, order (2,/) defined by P(?()are orthogonal onl (-1, 1) writh resplect tO ( 1 0x)at(1 ?
Askey, R., Wainger, S.
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Series concatenation of 2D convolutional codes
2015 IEEE 9th International Workshop on Multidimensional (nD) Systems (nDS), 2015In this paper we study two-dimensional (2D) con-volutional codes which are obtained from series concatenation of two 2D convolutional codes. In this preliminary work we confine ourselves to dealing with finite-support 2D convolutional codes and make use of the so-called Fornasini-Marchesini input-state-output (ISO) model representations. In particular,
Joan-Josep Climent +3 more
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Convolutional Neural Networks with Dynamic Convolution for Time Series Classification
2021Due to its prominent applications, time series classification is one of the most important fields of machine learning. Although there are various approaches for time series classification, dynamic time warping (DTW) is generally considered to be a well-suited distance measure for time series.
Krisztián Búza, Margit Antal
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