Using Input-Output Hidden Markov Models for the Aggregation of Performance Models

Input-Output Hidden Markov Models for the Aggregation of Performance Models

— This paper reports about experiments on generating aggregates for performance (sub)models. The aggregates are described by Input-Output Hidden Markov Models (IOHMMs). The parameters of the IOHMM are calculated from observation sequences obtained from the in-put/output behaviour of the original (sub)model.

Introducing Busy Customer Portfolio Using Hidden Markov Model

Due to the effective role of Markov models in customer relationship management (CRM), there is a lack of comprehensive literature review which contains all related literatures. In this paper the focus is on academic databases to find all the articles that had been published in 2011 and earlier. One hundred articles were identified and reviewed to find direct relevance for applying Markov models...

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words

Pattern Classi cation Using Hidden Markov Models

Input/output performance on current parallel le systems is sensitive to a good match of application access pattern to le system capabilities. Automatic input/output access classiication can determine application access patterns at execution time, guiding adaptive le system policies. In this paper we examine a new method for access pattern classiication that uses hidden Markov models, trained on...