DocumentCode
1745615
Title
Context dependent ARMA modeling
Author
Shmilovici, A. ; Ben-Gal, I.
Author_Institution
Dept. of Ind. Eng. & Manage., Ben-Gurion Univ. of the Negev, Beer-Sheva, Israel
fYear
2000
fDate
2000
Firstpage
249
Lastpage
252
Abstract
We propose to extend the use of Risannen´s (1983) “tree source”-a relative of the partial hidden Markov model-to continuous signals. While the original algorithm is dedicated to modeling the context in which each symbol can occur in a discrete symbol space, we propose to match a specific ARMA model with each identified context. An example is presented
Keywords
autoregressive moving average processes; hidden Markov models; signal processing; Box Jenkins series; Risannen´s tree source; autoregressive moving average; chemical process viscosity readings; context dependent ARMA modeling; continuous signals; discrete symbol space; nonlinear process; partial hidden Markov model; signal processing; Automata; Chemical processes; Context modeling; Engineering management; Explosives; Hidden Markov models; Industrial engineering; Predictive models; Process control; Viscosity;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical and electronic engineers in israel, 2000. the 21st ieee convention of the
Conference_Location
Tel-Aviv
Print_ISBN
0-7803-5842-2
Type
conf
DOI
10.1109/EEEI.2000.924382
Filename
924382
Link To Document