IEEE Transactions on Information Theory · 1992 · 150 citations · 22 references
EngineeringInformation ForensicsMarkov Decision ProcessesStochastic AnalysisStochastic SimulationMarkov ChainsData ScienceHidden Markov ModelStochastic ProcessesMinimum DegreesFinite-state Markov ChainStatisticsKolmogorov ComplexityInformation TheoryStochastic SystemMarkov ProcessesKnowledge DiscoveryData PrivacyStochastic NetworksDifferent Markov ChainsProbability TheoryComputer ScienceFinite-state SystemStochastic ModelingProcess DynamicsEntropyNatural SciencesMarkov KernelMarkov Transition MatrixStatistical Inference
If only a function of the state in a finite-state Markov chain is observed, then the stochastic process is no longer Markovian in general. This type of information source is found widely and the basic problem of its identifiability remains open, that is, the problem of showing when two different Markov chains generate the same stochastic process. The identifiability problem is completely solved by linear algebra, where a block structure of a Markov transition matrix plays a fundamental role, and from which the minimum degree of freedom for a source is revealed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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<i>Applications of the Theory of Matrices</i>
Felix R. Gantmacher, J. L. Brenner, D. W. Bushaw et al. · Physics Today · 1960 · 697 citations
The topology of spaces of rational functions
Graeme Segal · Acta Mathematica · 1979 · 287 citations · Full text
Set-theoretic Topology, Topological Algebra, Topological Property +2
A Markovian Function of a Markov Chain
C. J. Burke, M. Rosenblatt · The Annals of Mathematical Statistics · 1958 · 268 citations · Full text
Ira Pohl, Michael A. Arbib · Mathematics of Computation · 1970 · 198 citations