Analyzing Markov Chains using Kronecker Products Theory and Applications /
Kronecker products are used to define the underlying Markov chain (MC) in various modeling formalisms, including compositional Markovian models, hierarchical Markovian models, and stochastic process algebras. The motivation behind using a Kronecker structured representation rather than a flat one is...
保存先:
| 第一著者: | |
|---|---|
| 団体著者: | |
| フォーマット: | 電子媒体 eBook |
| 言語: | English |
| 出版事項: |
New York, NY :
Springer New York : Imprint: Springer,
2012.
|
| 版: | 1st ed. 2012. |
| シリーズ: | SpringerBriefs in Mathematics,
|
| 主題: | |
| オンライン･アクセス: | https://doi.org/10.1007/978-1-4614-4190-8 |
| タグ: |
タグ追加
タグなし, このレコードへの初めてのタグを付けませんか!
|
目次:
- Introduction
- Background
- Kronecker representation
- Preprocessing
- Block iterative methods for Kronecker products
- Preconditioned projection methods
- Multilevel methods
- Decompositional methods
- Matrix analytic methods.