Results 21 to 30 of about 1,945,411 (275)
Entropy, 2016 In this work, we propose a new approach of deriving the bounds between entropy and error from a joint distribution through an optimization means. The specific case study is given on binary classifications.
Bao-Gang Hu, Hong-Jie Xing
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On approximating the error function
Journal of Inequalities and Applications, 2016 In the article, we present the necessary and sufficient condition for the parameter p on the interval ( 7 / 5 , ∞ ) $(7/5, \infty)$ such that the function x → erf ( x ) / B p ( x ) $x\rightarrow\operatorname{erf}(x)/B_{p}(x)$ is strictly increasing ...
Zhen-Hang Yang, Yu-Ming Chu
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Fidelity of a t-error correcting quantum code with more than t errors [PDF]
, 2000 It is important to study the behavior of a t-error correcting quantum code when the number of errors is greater than t, because it is likely that there are also small errors besides t large correctable errors.
Matsumoto, Ryutaroh
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Fractal and Fractional, 2022 This paper investigates the switching-jumps-dependent quasi-synchronization issue for fractional-order memristive neural networks (FMNNs). First, a simplied linear feedback controller is applied.
Yingjie Fan, Zhongliang Wei, Meixuan Li
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Error bound analysis and singularly perturbed Abel-Volterra equations
Journal of Applied Mathematics, 2004 Asymptotic solutions of nonlinear singularly perturbed Volterra integral equations with kernels possessing integrable singularity are investigated using singular perturbation methods and the Mellin transform technique.
Angelina M. Bijura
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Mathematics, 2021 A classical reduced order model (ROM) for dynamical problems typically involves only the spatial reduction of a given problem. Recently, a novel space–time ROM for linear dynamical problems has been developed [Choi et al., Space–tume reduced order model ...
Youngkyu Kim, Karen Wang, Youngsoo Choi
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Error bound of the multilevel adaptive cross approximation (MLACA) [PDF]
, 2016 An error bound of the multilevel adaptive cross approximation (MLACA 1, which is a multilevel version of the adaptive cross approximation-singular value decomposition (ACA-SVD), is rigorously derived.
Cao, Qunsheng +4 more
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Global Continuous Optimization with Error Bound and Fast Convergence [PDF]
, 2015 This paper considers global optimization with a black-box unknown objective function that can be non-convex and non-differentiable. Such a difficult optimization problem arises in many real-world applications, such as parameter tuning in machine learning,
Kawaguchi, Kenji +2 more
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Bounds on decoherence and error [PDF]
Physical Review A, 1998 When a confined system interacts with its walls (treated quantum mechanically), there is an intertwining of degrees of freedom. We show that this need not lead to entanglement, hence decoherence. It will generally lead to error. The wave function optimization required to avoid decoherence is also examined.
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A Familiartiy-Based Bound on the Expected Error Rate for Classification with the Fuzzy ARTMAP Neural Network [PDF]
, 1999 We obtain a bound on the expected error rate of the fuzzy ARTMAP neural network employed as a classifier. This bound is based on leave-one-out estimation of the classification error, and is analogous to a bound on the expected error rate for support ...
Rubin, Mark
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