Optimal Segmentation of Random Sequences
Volume 11, Issue 3 (2000), pp. 243–256
Pub. online: 1 January 2000
Type: Research Article
Received
1 July 2000
1 July 2000
Published
1 January 2000
1 January 2000
Abstract
This paper deals with maximum likelihood and least square segmentation of autoregressive random sequences with abruptly changing parameters. Conditional distribution of the observations has been derived. Objective function was modified to the form suitable to apply dynamic programming method for its optimization. Expressions of Bellman functions for this case were obtained. Performance of presented approach is illustrated with simulation examples and segmentation of speech signals examples.