Results 51 to 60 of about 4,267,953 (306)
Quantitative sum rule analysis of low-temperature spectral functions [PDF]
, 2013 We analyze QCD and Weinberg-type sum rules in a low-temperature pion gas using vector and axial-vector spectral functions following from the model-independent chiral-mixing scheme.
Hohler, Paul M. +2 more
core +3 more sources
Vector mesons in nuclear medium with small three momentum, a QCD sum rule approach [PDF]
, 1998 Using the QCD Operator Product Expansion, we derive the real part of the transverse and longitudinal vector vector correlation function with the $\rho,\omega$ quantum numbers to leading order in density and in ${\bf q}^2$ at $-\omega^2\to \infty $.
Agakichiev +17 more
core +2 more sources
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2021 Due to the wide use of multi-sensor technology, analysis of multiple sets of data is at the heart of many challenging engineering problems. Independent vector analysis (IVA), a recent generalization of independent component analysis (ICA), enables the ...
Lucas P. Damasceno +3 more
semanticscholar +1 more source
Preserving Subject Variability in Group fMRI Analysis: Performance Evaluation of GICA versus IVA
Frontiers in Systems Neuroscience, 2014 Independent component analysis (ICA) is a widely applied technique to derive functionally connected brain networks from fMRI data. Group ICA (GICA) and Independent Vector Analysis (IVA) are extensions of ICA that enable users to perform group fMRI ...
Andrew eMichael +6 more
doaj +1 more source
Superluminal Vector in Ghost-free Massive Gravity [PDF]
, 2014 We present a classical analysis on the issue of vector superluminality in the decoupling limit ghost-free massive gravity with a Minkowski reference metric. We show explicitly in the Lorenz gauge that the theory is free of superluminal vector excitations
Yu, Siqing
core +2 more sources
Independent Vector Analysis via Log-Quadratically Penalized Quadratic Minimization [PDF]
IEEE Transactions on Signal Processing, 2020 We propose a new algorithm for blind source separation (BSS) using independent vector analysis (IVA). This is an improvement over the popular auxiliary function based IVA (AuxIVA) with iterative projection (IP) or iterative source steering (ISS).
Robin Scheibler
semanticscholar +1 more source
Blind Audio Source Separation Using Independent Component Analysis and Independent Vector Analysis
International Journal of Applied Mathematics, Electronics and Computers, 2016 Blind Source Separation (BSS) is one of the most important andchallenging problem for the researchers in audio and speech processing area. Inthe literature, many different methods have been proposed to solve BSS problem.In this study, we have compared the performance of three popular BSS methodsbased on Independent Component Analysis (ICA) and ...
MAHDİ, Alyaa +2 more
openaire +5 more sources
Fourth Moments and Independent Component Analysis [PDF]
, 2015 In independent component analysis it is assumed that the components of the observed random vector are linear combinations of latent independent random variables, and the aim is then to find an estimate for a transformation matrix back to these ...
Miettinen, Jari +3 more
core +1 more source
Independent Component Analysis and Number of Independent Basis Vectors
Procedia Computer Science, 2015 AbstractAmong the various biometric systems, face recognition is an important area of research due to its applications in Human Computer Interaction, biometrics and security. It is one of the most popular research areas in the field of computer vision and pattern recognition.
Borade, Sushma Niket +2 more
openaire +1 more source
SVM Based on Gaussian and Non-Gaussian Double Subspace for Fault Detection
IEEE Access, 2021 In industrial production processes, the data usually have high-dimensional characteristics. When a support vector machine (SVM) is used for fault detection, it takes a long time to run.
Jinyu Guo, Tao Li, Yuan Li
doaj +1 more source