Results 21 to 30 of about 33,561,195 (290)
Multimodal Image Reconstruction of Electrical Impedance Tomography Using Kernel Method
IEEE Transactions on Instrumentation and Measurement, 2022 The inverse problem of electrical impedance tomography (EIT) is nonlinear and severely ill-posed, resulting in low image quality, which explicitly involves the aspects of structure preservation and conductivity contrast differentiation.
Zhe Liu, Yunjie Yang
semanticscholar +1 more source
Biologically-Inspired Pulse Signal Processing for Intelligence at the Edge
Frontiers in Artificial Intelligence, 2021 There is an ever-growing mismatch between the proliferation of data-intensive, power-hungry deep learning solutions in the machine learning (ML) community and the need for agile, portable solutions in resource-constrained devices, particularly for ...
Kan Li, José C. Príncipe
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Unlabeled $(2+2)$-free posets, ascent sequences and pattern avoiding permutations [PDF]
Discrete Mathematics & Theoretical Computer Science, 2009 We present statistic-preserving bijections between four classes of combinatorial objects. Two of them, the class of unlabeled $(\textrm{2+2})$-free posets and a certain class of chord diagrams (or involutions), already appeared in the literature, but ...
Mireille Bousquet-Mélou +3 more
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Mathematics, 2022 In this study, a multiscale monitoring method for nonlinear processes was developed. We introduced a machine learning tool for fault detection and isolation based on the kernel principal component analysis (PCA) and discrete wavelet transform.
Hanen Chaouch +4 more
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A Kernel Method for the Two-Sample-Problem [PDF]
Neural Information Processing Systems, 2006 We propose two statistical tests to determine if two samples are from different distributions. Our test statistic is in both cases the distance between the means of the two samples mapped into a reproducing kernel Hilbert space (RKHS).
A. Gretton +4 more
semanticscholar +1 more source
Wilf classification of triples of 4-letter patterns I [PDF]
Discrete Mathematics & Theoretical Computer Science, 2017 This paper is first part of a complete paper in arXiv , see 1605.04969.
David Callan +2 more
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Nonparametric Estimation of the Expected Shortfall Regression for Quasi-Associated Functional Data
Mathematics, 2022 In this paper, we study the nonparametric estimation of the expected shortfall regression when the exogenous observation is functional. The constructed estimator is obtained by combining the double kernels estimator of both conditional value at risk and ...
Larbi Ait-Hennani +3 more
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Scalar-on-Function Relative Error Regression for Weak Dependent Case
Axioms, 2023 Analyzing the co-variability between the Hilbert regressor and the scalar output variable is crucial in functional statistics. In this contribution, the kernel smoothing of the Relative Error Regression (RE-regression) is used to resolve this problem ...
Zouaoui Chikr Elmezouar +5 more
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The kernel polynomial method [PDF]
Reviews of Modern Physics, 2006 Efficient and stable algorithms for the calculation of spectral quantities and correlation functions are some of the key tools in computational condensed matter physics. In this article we review basic properties and recent developments of Chebyshev expansion based algorithms and the Kernel Polynomial Method.
Weiße, Alexander +3 more
openaire +2 more sources
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2022 Automatic seizure detection system can serve as a meaningful clinical tool for the treatment and analysis of epilepsy using electroencephalogram (EEG) and has obtained rapid development.
Shasha Yuan +6 more
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