Results 81 to 90 of about 281 (133)
Journal of Applied MathematicsThis work is aimed at deriving a computationally efficient approach to approximate the second-order Index-1 descriptor systems without exploiting the fundamental structure of the systems, which ensures both the accuracy of the approximation and the ...
Mahtab Uddin +2 more
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Journal of Applied Mathematics, 2012 We study the preconditioned iterative method for the unsteady Navier-Stokes equations. The rotation form of the Oseen system is considered. We apply an efficient preconditioner which is derived from the Hermitian/Skew-Hermitian preconditioner to the ...
Jia Liu
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Estimating the numerical range with a Krylov subspace
CoRRKrylov subspace methods are a powerful tool for efficiently solving high-dimensional linear algebra problems. In this work, we study the approximation quality that a Krylov subspace provides for estimating the numerical range of a matrix. In contrast to prior results, which often depend on the gaps between eigenvalues, our estimates depend only on the ...
Cecilia Chen, John Urschel
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한국해양공학회지Recently, digital transformation has become crucial for the safe operation and extended lifespan of ships and offshore structures. Structural health management is gaining importance and driving interest in digital twin technology for monitoring ...
Kichan Sim +3 more
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Nuclear Engineering and TechnologyDiscrete ordinates (SN) method with unstructured meshes is highly appropriate for high-fidelity modeling and simulation of radiation shielding problems with complicated geometries.
Ao Zhang +3 more
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Neural preconditioning via Krylov subspace geometry
Bollettino dell'Unione Matematica ItalianaAbstract We propose a geometry-aware strategy for training neural preconditioners tailored to parametrized linear systems arising from the discretization of mixed-dimensional partial differential equations (PDEs). Such systems are typically ill-conditioned due to embedded lower-dimensional structures and are solved using Krylov ...
Nunzio Dimola +2 more
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Deterministic sketching for Krylov subspace methods
CoRRRandomized sketching is currently introduced into every area of numerical linear algebra. In Krylov subspace methods, it allows runtime savings at the cost of small accuracy reductions. This work offers a different view on sketching in Krylov methods by analyzing what subspace embeddings are obtained by arbitrary sketching matrices.
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Investigating Multi-Array Antenna Signal Convergence using Wavelet Transform and Krylov Sequence
Mehran University Research Journal of Engineering and Technology, 2018 In the present world, wireless communication is becoming immensely popular for plethora of applications. Technology has been advancing at an accelerated rate leading to make communication reliable.
Muhammad Ahmed Sikander +2 more
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Convergence of restarted Krylov subspaces to invariant subspaces
, 2016 The performance of Krylov subspace eigenvalue algorithms for large matrices can be measured by the angle between a desired invariant subspace and the Krylov subspace. We develop general bounds for this convergence that include the effects of polynomial restarting and impose no restrictions concerning the diagonalizability of the matrix or its degree of
Beattie, C, Embree, M, Rossi, J
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Network Analysis Using Krylov Subspace Trajectories
We describe a set of network analysis methods based on the rows of the Krylov subspace matrix computed from a network adjacency matrix via power iteration using a non-random initial vector. We refer to these node-specific row vectors as Krylov subspace trajectories. While power iteration using a random initial starting vector is commonly applied to the
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