Results 61 to 70 of about 16,895 (156)
A Discretized Tikhonov Regularization Method for a Fractional Backward Heat Conduction Problem
Abstract and Applied Analysis, 2014 We propose a numerical reconstruction method for solving a time-fractional backward heat conduction problem. Based on the idea of reproducing kernel approximation, we reconstruct the unknown initial heat distribution from a finite set of scattered ...
Zhi-Liang Deng, Xiao-Mei Yang
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INFORMATIVE ENERGY METRIC FOR SIMILARITY MEASURE IN REPRODUCING KERNEL HILBERT SPACES [PDF]
International Journal of Computational Intelligence Systems, 2012 In this paper, information energy metric (IEM) is obtained by similarity computing for high-dimensional samples in a reproducing kernel Hilbert space (RKHS).
Songhua Liu, Junying Zhang, Caiying Ding
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Representing functional data in reproducing Kernel Hilbert Spaces with applications to clustering and classification [PDF]
, 2010 Functional data are difficult to manage for many traditional statistical techniques given their very high (or intrinsically infinite) dimensionality. The reason is that functional data are essentially functions and most algorithms are designed to work ...
González, Javier, Muñoz, Alberto
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Climate change and crop resilience: harnessing metabolomics for predicting stress tolerance
New Phytologist, EarlyView.Summarised methodology for metabolite biomarker discovery and genomic targets selection for those metabolites to predict high‐throughput phenotypic and agronomic traits of interest for direct uptake in breeding programmes. Summary Global warming is driving climate change to levels not experienced since the advent of agriculture, primarily due to ...
Agyeya Pratap +3 more
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Reproducing Kernel Method for Solving Nonlinear Differential-Difference Equations
Abstract and Applied Analysis, 2012 On the basis of reproducing kernel Hilbert spaces theory, an iterative algorithm for solving some nonlinear differential-difference equations (NDDEs) is presented.
Reza Mokhtari +2 more
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Mathematical Modelling and Analysis, 2015 An iterative method is discussed with respect to its effectiveness and capability of solving singular nonlinear Lane-Emden type equations using reproducing kernel Hilbert space method combined with the Picard iteration.
Babak Azarnavid +2 more
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Spatial depth for data in metric spaces
Scandinavian Journal of Statistics, EarlyView.Abstract We propose a novel measure of statistical depth, the metric spatial depth, for data residing in an arbitrary metric space. The measure assigns high (low) values for points located near (far away from) the bulk of the data distribution, allowing quantifying their centrality/outlyingness.
Joni Virta
wiley +1 more source
On the weak limit of compact operators on the reproducing kernel Hilbert space and related questions
Analele Stiintifice ale Universitatii Ovidius Constanta: Seria Matematica, 2016 By applying the so-called Berezin symbols method we prove a Gohberg- Krein type theorem on the weak limit of compact operators on the non- standard reproducing kernel Hilbert space which essentially improves the similar results of Karaev [5]: We also in ...
Saltan Suna
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Reproducing Kernel Method with Global Derivative
Journal of Function Spaces, 2023 Ordinary differential equations describe several phenomena in different fields of engineering and physics. Our aim is to use the reproducing kernel Hilbert space method (RKHSM) to find a solution to some ordinary differential equations (ODEs) that are ...
Nourhane Attia +2 more
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Regularized system identification using orthonormal basis functions
, 2015 Most of existing results on regularized system identification focus on regularized impulse response estimation. Since the impulse response model is a special case of orthonormal basis functions, it is interesting to consider if it is possible to tackle ...
Chen, Tianshi, Ljung, Lennart
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