Results 1 to 10 of about 240,394 (261)
Recurrent sequences and Schur functions
Advances in Applied Mathematics, 2003 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Qing-Hu Hou, Yan-Ping Mu
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On Third-Order Linear Recurrent Functions
Discrete Dynamics in Nature and Society, 2019 A function ψ:R→R is said to be a Tribonacci function with period p if ψ(x+3p)=ψ(x+2p)+ψ(x+p)+ψ(x), for all x∈R. In this paper, we present some properties on the Tribonacci functions with period p. We show that if ψ is a Tribonacci function with period p,
Kodjo Essonana Magnani
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Recurrent identities for two special functions of hypergeometric type
Вестник Самарского университета: Естественнонаучная серия, 2023 The article presents conclusions and proofs of Gauss-type identities for two known hypergeometric type functions. For the derivation and justification of formulas, the representation of functions in the form of a series is used, as well as an integral ...
Svetlana V. Podkletnova
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Recurrence Relations for Orthogonal Functions [PDF]
, 2020 When µ is a finite (positive) Borel measure with infinite support on T or R (with suitable restrictions), positive definite functionals M (and thereby positive definite inner products) are defined through M(f)=∫_{-π..π}f(e^{it})dµ(t) in the circle-disk situation, and M(f)=∑_{-∞..∞}f(t)dµ(t) in the line-plane situation.
Bultheel, Adhemar +3 more
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Eigenpairs for the Analysis of Complete Lyapunov Functions
Complexity, 2022 A complete Lyapunov function describes the qualitative behaviour of a dynamical system: the areas where the orbital derivative vanishes and where it is strictly negative characterise the chain recurrent set and the gradient-like flow, respectively ...
Carlos Argáez +2 more
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Generalized Almost Periodicity in Lebesgue Spaces with Variable Exponents
Mathematics, 2020 In this paper, we introduce and analyze Stepanov uniformly recurrent functions, Doss uniformly recurrent functions and Doss almost-periodic functions in Lebesgue spaces with variable exponents.
Marko Kostić, Wei-Shih Du
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CoRR, 2019 Despite recent successes in Reinforcement Learning, value-based methods often suffer from high variance hindering performance. In this paper, we illustrate this in a continuous control setting where state of the art methods perform poorly whenever sensor noise is introduced.
Pierre Thodoroff +4 more
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Recurrent neural network wave functions
Physical Review Research, 2020 A core technology that has emerged from the artificial intelligence revolution is the recurrent neural network (RNN). Its unique sequence-based architecture provides a tractable likelihood estimate with stable training paradigms, a combination that has ...
Mohamed Hibat-Allah +4 more
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ON THE GROWTH OF LINEAR RECURRENCES IN FUNCTION FIELDS [PDF]
Bulletin of the Australian Mathematical Society, 2020 AbstractLet $ (G_n)_{n=0}^{\infty } $ be a nondegenerate linear recurrence sequence whose power sum representation is given by $ G_n = a_1(n) \alpha _1^n + \cdots + a_t(n) \alpha _t^n $ . We prove a function field analogue of the well-known result in the number field case that, under some nonrestrictive conditions, $ |{G_n}| \geq ( \max _{j=1 ...
CLEMENS FUCHS, SEBASTIAN HEINTZE
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GCRNN: graph convolutional recurrent neural network for compound–protein interaction prediction
BMC Bioinformatics, 2022 Background Compound–protein interaction prediction is necessary to investigate health regulatory functions and promotes drug discovery. Machine learning is becoming increasingly important in bioinformatics for applications such as analyzing protein ...
Ermal Elbasani +5 more
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