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Grigoletto et al., 2023 - Google Patents

Algebraic reduction of hidden markov models

Grigoletto et al., 2023

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Document ID
8922150967826979871
Author
Grigoletto T
Ticozzi F
Publication year
Publication venue
IEEE Transactions on Automatic Control

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Snippet

The problem of reducing a hidden Markov model (HMM) to one of smaller dimension that exactly reproduces the same marginals is tackled by using a system-theoretic approach. Realization theory tools are extended to HMMs by leveraging suitable algebraic …
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    • G—PHYSICS
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    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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    • G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6251—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on a criterion of topology preservation, e.g. multidimensional scaling, self-organising maps
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