Dependency as a measure to estimate the order and the values of Markov processes

DOI10.1007/BF01885639zbMath0353.62047OpenAlexW2067789151MaRDI QIDQ1236398

Hisashi Fujii, Naohiro Ishii, Kojiro Aya, Hiroshi Nakahama, Mitsuaki Yamamoto

Publication date: 1977

Published in: Biological Cybernetics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf01885639

Mathematics Subject Classification ID

Markov processes: estimation; hidden Markov models (62M05) Discrete-time Markov processes on general state spaces (60J05)

Related Items (6)

Wiener analysis of functionals of a Markov chain: Application to neural transformations of random signals ⋮ Nonhomogeneous Markov chains with desired properties - the nearest Markovian model ⋮ Testing the order of discrete Markov chains using surrogate data ⋮ Modeling Markovian biological systems via optimization operators ⋮ Dependency representing Markov properties of nonstationary spike trains recorded from the cat's optic tract fibers ⋮ A maximum entropy criterion of filtering and coding for stationary autoregressive signals: Its physical interpretations and suggestions for its application to neural information transmission

Cites Work

• Statistical dependency as a measure to evaluate Markov properties of stochastic point processes
• Statistical inference on markov process of neuronal impulse sequences
• Effects of Configuration Interaction on Intensities and Phase Shifts
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