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Sparse Minimum Redundancy Maximum Relevance for Feature Selection
ABSTRACT We propose a feature screening method that integrates both feature–feature and feature–target relationships. Inactive features are identified via a penalized minimum Redundancy Maximum Relevance (mRMR) procedure, which is the continuous version of the classical mRMR penalized by a non‐convex regularizer, and where the parameters estimated as ...
Peter Naylor +3 more
wiley +1 more source
RKHS approach for signal detection in rotation and scale space random fields [PDF]
Two important papers of Worsley, Siegmund and coworkers consider rotation and scale space random fields for detecting signals in fMRI (functional magnetic resonance imaging) brain images. They use the global maxima of images for detection of a signal. In
K. Shafie, Akbar Abravesh
doaj +1 more source
How to Match Cognitive Model Predictions With EEG Data
Abstract Reliably identifying relevant brain areas implicated by the simulated activity from cognitive models is still an unsolved problem for cognitive modeling, particularly when matching model output with human electroencephalography (EEG) data. We propose a new method involving postprocessing of ACT‐R module activity and clustered EEG component ...
Kai Preuss +3 more
wiley +1 more source
Abstact figure legend A panoramic 3D optical mapping system was developed, enabling imaging of action potential waves across the entire strongly deforming ventricular surface of beating isolated hearts. The system comprises 12 high‐speed cameras and a soccerball‐shaped imaging chamber with 48 light‐emitting diodes (LEDs).
Shrey Chowdhary +5 more
wiley +1 more source
Abstract figure legend Comparative multimodal calibration of patient‐specific left atrial (LA) models to identify arrhythmogenic substrates in atrial fibrillation (AF). A, LA models shown in posterior and anterior views, calibrated separately using: late gadolinium enhancement magnetic resonance imaging (LGE‐MRI) image intensity ratio (IIR; blue–red ...
Mahmoud Ehnesh +14 more
wiley +1 more source
Shot‐Based Quantum Encoding: A Data‐Loading Paradigm for Quantum Neural Networks
Shot‐based quantum encoding loads classical data without any encoding gates: a learned map turns each datum into a probability vector that dictates how many measurement shots start in each basis state, preparing a mixed state that a shallow variational circuit processes as a quantum perceptron layer.
Basil Kyriacou +3 more
wiley +1 more source
The present paper emphasizes Jeffery-Hamel flow: fluid flow between two rigid plane walls, where the angle between them is 2α. A new method called the reproducing kernel Hilbert space method (RKHSM) is briefly introduced.
Mustafa Inc +2 more
doaj +1 more source
Skew-symmetric and essentially unitary operators via Berezin symbols
We characterize skew-symmetric operators on a reproducing kernel Hilbert space in terms of their Berezin symbols. The solution of some operator equations with skew-symmetric operators is studied in terms of Berezin symbols.
Altwaijry Najla +3 more
doaj +1 more source
Abstract Multispectral three‐dimensional (3D) imaging offers substantial potential for plant phenotyping, yet manual segmentation of plant organs remains a bottleneck in breeding programs. We developed a color‐based filtering workflow for faba bean (Vicia faba L.) point clouds that optimizes lower and upper thresholds of spectral indices and broadband ...
Lennart Scheer +6 more
wiley +1 more source
Frequency‐dependent contraction rates for the Bayesian method to the inverse source problem
Abstract This paper addresses an inverse source problem for acoustic waves in a range of frequencies. Our study has two main goals. First, although the problem is severely ill‐posed with a logarithmic stability estimate, we demonstrate, through careful analysis of the forward map's singular values, that increasing the frequency range enhances stability,
Pu‐Zhao Kow, Jenn‐Nan Wang
wiley +1 more source

