A Vector Representation of Multicomplex Numbers and Its Application to Radio Frequency Signals
AxiomsHypercomplex numbers, which are multi-dimensional extensions of complex numbers, have been proven beneficial in the development of advanced signal processing algorithms, including multi-dimensional filter design, linear regression and classification.
Daniele Borio
doaj +1 more source
M-estimator, and D-optimality model construction using orthogonal forward regression [PDF]
, 2005 This correspondence introduces a new orthogonal forward regression (OFR) model identification algorithm using D-optimality for model structure selection and is based on an M-estimators of parameter estimates.
Hong, X., Chen, S.
core +1 more source
An epithelial GPR35 isoform supports tumor‐associated transcriptional and metabolic phenotypes
FEBS Letters, EarlyView.GPR35 generates two functionally distinct isoforms with previously unresolved roles. GPR35‐short mediates immune‐cell chemotaxis, while GPR35‐long is enriched in colorectal cancer epithelium, where it supports increased metabolism, proliferation, and tumor‐associated transcriptional programs.
Jørgen D. Rønneberg +14 more
wiley +1 more source
A new class of orthogonal polynomials for solving logarithmic singular integral equations
Ain Shams Engineering Journal, 2020 In this note, we propose a new class of orthogonal polynomials (named Bachok–Hasham polynomials H1nk(x)), which is an extension of the Chebyshev polynomials.
H. Alhawamda +3 more
doaj +1 more source
Model Predictive Control of Nonlinear MIMO Systems Based on Adaptive Orthogonal Polynomial Networks
Elektronika ir Elektrotechnika, 2021 This paper considers a new design of model predictive control based on specific models in the form of adaptive orthogonal polynomial networks, built around a specially tailored basis of generalized orthogonal functions.
Marko T. Milojkovic +5 more
doaj +1 more source
Complex-valued symmetric radial basis function network for beamforming [PDF]
, 2009 The complex-valued radial basis function (RBF) network proposed by Chen et al. (1994) has found many applications for processing complex-valued signals, in particular, for communication channel equalization and signal detection.
Sheng Chen, Chen, Sheng
core +1 more source
Interpreting the effects of DNA polymerase variants at the structural level
Molecular Oncology, EarlyView.Using MAVISp and molecular dynamics simulations, we analyzed over 60 000 missense variants in POLE and POLD1 from ClinVar, COSMIC, cBioPortal, and saturation mutagenesis. Identified mechanistic indicators, including stability, binding, and long‐range, enable structural interpretation, providing ACMG‐like evidence for possible reclassification of VUS ...
Matteo Arnaudi +7 more
wiley +1 more source
Orthogonal Basis Functions over the Binocular Pupil
Open Astronomy, 2010 Sets of orthogonal basis functions over circular areas - pupils in optical applications - are known in the literature for the full circle (Zernike or Jacobi polynomials) and the annulus.
Mathar Richard J.
doaj +1 more source
Combined genetic algorithm optimization and regularized orthogonal least squares learning for radial basis function networks [PDF]
, 1999 The paper presents a two-level learning method for radial basis function (RBF) networks. A regularized orthogonal least squares (ROLS) algorithm is employed at the lower level to construct RBF networks while the two key learning parameters, the ...
Luk, B.L., Wu, Y., Chen, S.
core
On combination of SMOTE and particle swarm optimization based radial basis function classifier for imbalanced problems [PDF]
, 2011 The combination of the synthetic minority oversampling technique (SMOTE) and the radial basis function (RBF) classifier is proposed to deal with classification for imbalanced two-class data.
Xia Hong +10 more
core +1 more source