Results 51 to 60 of about 16,895 (156)
Overlap-Kernel EPI: Estimating MRI Shot-to-Shot Phase Variations by Shifted-Kernel Extraction From Overlap Regions at Arbitrary k-Space Locations. [PDF]
Magn Reson MedABSTRACT Purpose In multi‐shot EPI, shot‐dependent phase fluctuations can introduce ghost artifacts, undermining advantages for enhancing resolution or reducing distortion, particularly in diffusion scans. Here, a novel self‐navigation strategy based on shift‐invariant kernel extraction is proposed, enabling robust estimation of phase inconsistencies ...
Tian R +3 more
europepmc +2 more sources
International Journal of Robust and Nonlinear Control, EarlyView.ABSTRACT Data‐based learning of system dynamics allows model‐based control approaches to be applied to systems with partially unknown dynamics. Gaussian process regression is a preferred approach that outputs not only the learned system model but also the variance of the model, which can be seen as a measure of uncertainty.
Daniel Landgraf +2 more
wiley +1 more source
Social Sustainability in Circular Bioeconomy Business Models: Insights From Argentina
Sustainable Development, EarlyView.ABSTRACT Research on circular bioeconomy business models (CBEBM) has largely prioritised environmental and economic aspects, leaving out the social pillar. To address this gap, this paper analyses to what extent and in what ways social sustainability is integrated into CBEBM, based on 12 cases from northern Argentina, a region with high potential for ...
Celina N. Amato +2 more
wiley +1 more source
Density Problem and Approximation Error in Learning Theory
Abstract and Applied Analysis, 2013 We study the density problem and approximation error of reproducing kernel Hilbert spaces for the purpose of learning theory. For a Mercer kernel on a compact metric space (, ), a characterization for the generated reproducing kernel Hilbert space (RKHS)
Ding-Xuan Zhou
doaj +1 more source
Combining kernelised autoencoding and centroid prediction for dynamic multi‐objective optimisation
CAAI Transactions on Intelligence Technology, EarlyView.Abstract Evolutionary algorithms face significant challenges when dealing with dynamic multi‐objective optimisation because Pareto optimal solutions and/or Pareto optimal fronts change. The authors propose a unified paradigm, which combines the kernelised autoncoding evolutionary search and the centroid‐based prediction (denoted by KAEP), for solving ...
Zhanglu Hou +4 more
wiley +1 more source
The oscillatory response of the electroretinogram and neuronal adaptation
Acta Ophthalmologica, EarlyView.Abstract After more than 50 years, there still remains a challenge and an interest to know more as well as extend and deepen our understanding of the small rapid wavelets, the oscillatory potentials (OPs), of the electroretinogram (ERG) and the neuronal adaptation of the retina.
Lillemor Wachtmeister, Anders Eklund
wiley +1 more source
Properties of Single-cycle Sinusoidal Wavelet Function
Journal of Harbin University of Science and TechnologyThe single-cycle sinusoidal wavelet is a wavelet with a compact support interval. In order to further study the properties of the single-cycle sinusoidal wavelet, based on the theory of wavelet analysis, the time-frequency analysis method is adopted to ...
LIN Qing +4 more
doaj +1 more source
Journal of Time Series Analysis, EarlyView.ABSTRACT Expectile is a coherent and elicitable law‐invariant risk measure widely applied in risk management. Existing methods based on iteratively reweighted least squares (IWLS) are not computationally efficient for large‐scale sample sizes. To overcome the issue, we develop a direct nonparametric conditional expectile function estimator by inverting
Feipeng Zhang, Ping‐Shou Zhong
wiley +1 more source
, 2011 A nonparametric kernel-based method for realizing Bayes' rule is proposed, based on representations of probabilities in reproducing kernel Hilbert spaces. Probabilities are uniquely characterized by the mean of the canonical map to the RKHS.
Fukumizu, Kenji +2 more
core +1 more source
Testing Distributional Granger Causality With Entropic Optimal Transport
Journal of Time Series Analysis, EarlyView.ABSTRACT We develop a novel nonparametric test for Granger causality in distribution based on entropic optimal transport. Unlike classical mean‐based approaches, the proposed method directly compares the full conditional distributions of a response variable with and without the history of a candidate predictor.
Tao Wang
wiley +1 more source