Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1154121 | Statistics & Probability Letters | 2008 | 4 Pages |
Abstract
We consider a generalized mixture of nonlinear AR models, a hidden Markov model for which the autoregressive functions are single layer feedforward neural networks. The nontrivial problem of identifiability, which is usually postulated for hidden Markov models, is addressed here.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Jean-Pierre Stockis, Joseph Tadjuidje-Kamgaing, Jürgen Franke,