Results 21 to 30 of about 251 (211)

Conditions for Singular Incidence Matrices [PDF]

open access: yesJournal of Algebraic Combinatorics, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +5 more sources

Application of an RBF blending interpolation method to problems with shocks

open access: yesComputer Assisted Methods in Engineering and Science, 2017
Radial basis functions (RBF) have become an area of research in recent years, especially in the use of solving partial differential equations (PDE). Radial basis functions have an impressive capability in interpolating scattered data, even for data with
Michael Harris   +2 more
doaj   +1 more source

Condition Numbers of Gaussian Random Matrices [PDF]

open access: yesSIAM Journal on Matrix Analysis and Applications, 2005
Let $G_{m \times n}$ be an $m \times n$ real random matrix whose elements are independent and identically distributed standard normal random variables, and let $κ_2(G_{m \times n})$ be the 2-norm condition number of $G_{m \times n}$. We prove that, for any $m \geq 2$, $n \geq 2$ and $x \geq |n-m|+1$, $κ_2(G_{m \times n})$ satisfies $ \frac{1}{\sqrt{2π}
Zizhong Chen, Jack J. Dongarra
openaire   +2 more sources

On the Numerical Approximation of Mobile-Immobile Advection-Dispersion Model of Fractional Order Arising from Solute Transport in Porous Media

open access: yesFractal and Fractional, 2022
The fractional mobile/immobile solute transport model has applications in a wide range of phenomena such as ocean acoustic propagation and heat diffusion.
Kamran   +5 more
doaj   +1 more source

Condition Numbers of Random Triangular Matrices [PDF]

open access: yesSIAM Journal on Matrix Analysis and Applications, 1998
It is shown that the 2-norm condition number of a lower triangular matrix of dimension \(n\), whose entries come from an independent normal variable of mean 0 and variance 1, grows exponentially with \(n\). This is in striking contrast to the linear growth of the condition number of random dense matrices.
D. Viswanath, Lloyd N. Trefethen
openaire   +2 more sources

A Novel Learning Algorithm Based on Bayesian Statistics: Modelling Thermostat Adjustments for Heating and Cooling in Buildings

open access: yesMathematics, 2022
The temperature of indoor spaces is at the core of highly relevant topics such as comfort, productivity and health. In conditioned spaces, this temperature is determined by thermostat preferences, but there is a lack of understanding of this phenomenon ...
Alfonso P. Ramallo-González   +3 more
doaj   +1 more source

Predisposal conditioning, treatment, and performance assessment of radioactive waste streams

open access: yesEPJ Nuclear Sciences & Technologies, 2022
Before the final disposal of radioactive wastes, various processes can be implemented to optimise the waste form. This can include different chemical and physical treatments, such as thermal treatment for waste reduction, waste conditioning for ...
Holt Erika   +7 more
doaj   +1 more source

On best conditioned matrices [PDF]

open access: yesProceedings of the American Mathematical Society, 1955
1. Main theorems. Let A be a positive definite Hermitian matrix of finite order, and let A and X be its maximal and minimal eigenvalue respectively. The condition number of A is the ratio P(A) =A/X introduced by Todd [1]. Let 'G be a class of regular linear transformations. Define ATT*A T. We say that A is best conditioned with respect to 'G if P(A T) >
Forsythe, G. E., Straus, E. G.
openaire   +1 more source

Advancing Text-to-Image Generation: A Comparative Study of StyleGAN-T and Stable Diffusion 3 under Neutrosophic Sets [PDF]

open access: yesNeutrosophic Sets and Systems
Recent advances in generative models have revolutionized the technology employed for image synthesis quite significantly, and two paradigms—GANs and diffusion-based models—are leading the pack of innovation.
Mohamed G Sadek   +3 more
doaj   +1 more source

Singular-Value-Decomposition-Based Matrix Surgery

open access: yesEntropy
This paper is motivated by the need to stabilise the impact of deep learning (DL) training for medical image analysis on the conditioning of convolution filters in relation to model overfitting and robustness.
Jehan Ghafuri, Sabah Jassim
doaj   +1 more source

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