Results 41 to 50 of about 7,065 (184)

Gram Decay and Intrinsic Dimensions of Krylov Subspaces

Numerical Linear Algebra with Applications, Volume 33, Issue 3, June 2026.
ABSTRACT Krylov subspace methods solve large sparse linear systems Ax=b$$ Ax=b $$ by building a sequence of polynomial approximations to A−1b$$ {A}^{-1}b $$ from successive matrix‐vector products. In finite precision, the number of numerically independent directions that can be extracted from this sequence is bounded by the intrinsic information ...
Stephen J. Thomas
wiley   +1 more source

A Distributed and Incremental SVD Algorithm for Agglomerative Data Analysis on Large Networks

, 2016
In this paper, we show that the SVD of a matrix can be constructed efficiently in a hierarchical approach. Our algorithm is proven to recover the singular values and left singular vectors if the rank of the input matrix $A$ is known.
Iwen, M. A., Ong, B. W.
core   +1 more source

Optimal Controller and Filter Realisations using Finite-precision, Floating- point Arithmetic. [PDF]

, 2005
The problem of reducing the fragility of digital controllers and filters implemented using finite-precision, floating-point arithmetic is considered.
Chen, Sheng, Gu, Da-Wei, Whidborne, James F., Wu, Jun   +3 more
core   +1 more source

Toward an Efficient Shifted Cholesky QR for Applications in Model Order Reduction Using pyMOR

Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.
ABSTRACT Many model order reduction (MOR) methods rely on the computation of an orthonormal basis of a subspace onto which the large full order model is projected. Numerically, this entails the orthogonalization of a set of vectors. The nature of the MOR process imposes several requirements for the orthogonalization process.
Maximilian Bindhak, Art J. R. Pelling, Jens Saak   +2 more
wiley   +1 more source

Comparison of five methods of computing the Dirichlet-Neumann operator for the water wave problem

, 2014
We compare the effectiveness of solving Dirichlet-Neumann problems via the Craig-Sulem (CS) expansion, the Ablowitz-Fokas-Musslimani (AFM) implicit formulation, the dual AFM formulation (AFM*), a boundary integral collocation method (BIM), and the ...
Vasan, Vishal, Wilkening, Jon
core   +1 more source

Fast computation of trimmed means [PDF]

, 2011
We present two methods of calculating trimmed means without sorting the data in O(n) time. The existing method implemented in major statistical packages relies on sorting, which takes O(n log n) time.
Beliakov, Gleb
core   +2 more sources

The Climate Modeling Alliance Atmosphere Dynamical Core: Concepts, Numerics, and Scaling

Journal of Advances in Modeling Earth Systems, Volume 18, Issue 3, March 2026.
Abstract This paper presents the dynamical core of the Climate Modeling Alliance (CliMA) atmosphere model, designed for efficient simulation of a wide range of atmospheric flows across scales. The core uses the nonhydrostatic equations of motion for a deep atmosphere, discretized with a hybrid approach that combines a spectral element method (SEM) in ...
Dennis Yatunin, Simon Byrne, Charles Kawczynski, Sriharsha Kandala, Gabriele Bozzola, Akshay Sridhar, Zhaoyi Shen, Anna Jaruga, Julia Sloan, Jia He, Daniel Zhengyu Huang, Valeria Barra, Ray Chew, Anudhyan Boral, Yi‐fan Chen, Oswald Knoth, Paul Ullrich, Cheikh Mbengue, Tapio Schneider   +18 more
wiley   +1 more source

A Practical pedestrian approach to parsimonious regression with inaccurate inputs [PDF]

Songklanakarin Journal of Science and Technology (SJST), 2014
A measurement result often dictates an interval containing the correct value. Interval data is also created by roundoff, truncation, and binning. We focus on such common interval uncertainty in data.
Seppo Karrila
doaj  

3D simulations of linearized scalar fields in Kerr spacetime [PDF]

, 2003
We investigate the behavior of a dynamical scalar field on a fixed Kerr background in Kerr-Schild coordinates using a 3+1 dimensional spectral evolution code, and we measure the power-law tail decay that occurs at late times.
A. Gullstrand, Adrienne L. Erickcek, B. Szilágyi, C. Gundlach, C.V. Vishveshwara, E. Poisson, E.S.C. Ching, G. Calabrese, G. Calabrese, H. Friedrich, Harald P. Pfeiffer, L. Barack, L. Barack, L. Lindblom, L.E. Kidder, L.E. Kidder, L.M. Burko, L.M. Burko, Lawrence E. Kidder, Lior M. Burko, M. Bjørhus, M.A. Scheel, Mark A. Scheel, N. Fröman, P. Painlevé, R.H. Price, S. Frittelli, S. Frittelli, S. Hod, Saul A. Teukolsky, W. Krivan, W. Krivan   +31 more
core   +3 more sources

Poisson count time series

Journal of Time Series Analysis, Volume 47, Issue 2, Page 279-303, March 2026.
This article reviews and compares popular methods, some old and some recent, that produce time series having Poisson marginal distributions. The article begins by narrating ways where time series with Poisson marginal distributions can be produced.
Jiajie Kong, Robert Lund
wiley   +1 more source