## Abstract Many very large Markov chains can be modelled efficiently as stochastic automata networks (SANs). A SAN is composed of individual automata which, for the most part, act independently, requiring only infrequent interaction. SANs represent the generator matrix __Q__ of the underlying Mark
Kronecker product approximation of demagnetizing tensors for micromagnetics
β Scribed by A.V. Goncharov; G. Hrkac; J.S. Dean; T. Schrefl
- Publisher
- Elsevier Science
- Year
- 2010
- Tongue
- English
- Weight
- 306 KB
- Volume
- 229
- Category
- Article
- ISSN
- 0021-9991
No coin nor oath required. For personal study only.
β¦ Synopsis
A comparison study of the asymptotic behavior between different compression techniques is reported. We show that by applying the Kronecker product approximation, the storage of a three-dimensional demagnetizing tensor with N 6 entries can be reduced to OΓ°N 2 Γ, showing a superlinear compression behavior. When magnetization and magnetostatic field vectors are stored in compressed forms, a superlinear speedup of a field evaluation is gained.
π SIMILAR VOLUMES
Krishnamurthy, E.V. and H. Schrrder, Systolic algorithm for multivariable approximation using tensor products of basis functions, Parallel Computing 17 (1991) 483-492, This paper describes a systolic algorithm based on tensor products of basis functions for multivariable approximation. Some implemen
The main result reads: if a nonsingular matrix A of order n = pq is a tensor-product binomial with two factors then the tensor rank of A -1 is bounded from above by min{p, q}.