Fuzzy Hidden Markov Chain Based Models for Time-Series Data

Author:

Tao Yihui,Mahfouf Mahdi

Publisher

Springer Nature Switzerland

Reference30 articles.

1. Elliott, R.J., Aggoun, L., Moore, J.B.: Hidden Markov Models: Estimation and Control, vol. 29. Springer, New York (2008)

2. Krishnamurthy, V., Djonin, D.V.: Structured threshold policies for dynamic sensor scheduling—a partially observed Markov decision process approach. IEEE Trans. Signal Process. 55(10), 4938–4957 (2007)

3. Basak, S.C., Magnuson, V.R.: Molecular topology and narcosis. A quantitative structure-activity relationship (QSAR) study of alcohols using complementary information content (CIC). Arzneimittel-Forschung/Drug Res. 33(4), pp.501–503 (1983)

4. Dongmei, Z., Jinxing, L.: Approach to forecasting multi-step attack based on fuzzy hidden Markov model. J. Appl. Sci. 13, 4955–4960 (2013)

5. Baum, L.E., Petrie, T.: Statistical inference for probabilistic functions of finite state Markov chains. Ann. Math. Stat. 37(6), 1554–1563 (1966)

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