Abstract
We propose an information-theoretic Markov aggregation framework that is motivated by two objectives: 1) The Markov chain observed through the aggregation mapping should be Markov. 2) The aggregated chain should retain the temporal dependence structure of the original chain. We analyze our parameterized cost function and show that it contains previous cost functions as special cases, which we critically assess. Our simple optimization heuristic for deterministic aggregations characterizes the optimization landscape for different parameter values.
Original language | English |
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Article number | 8861026 |
Pages (from-to) | 3068-3075 |
Number of pages | 8 |
Journal | IEEE Transactions on Automatic Control |
Volume | 65 |
Issue number | 7 |
DOIs | |
Publication status | Published - Jul 2020 |
Keywords
- Bisimulation
- information theory
- lumpability
- Markov chain
- model reduction
- predictability
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Computer Science Applications