Basecalling using hidden Markov models

Hidden Markov Models for Dna Sequencing

In this paper we propose Hidden Markov Models as an approach to the DNA basecalling problem. We model the state emission densities using Artificial Neural Networks, and provide a modified Baum-Welch re-estimation procedure to perform training. Moreover, we develop a method that exploits consensus sequences to label training data, thus minimizing the need for hand-labeling. Our results demonstra...

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

مدل سازی فضایی-زمانی وقوع و مقدار بارش زمستانه در گستره ایران با استفاده از مدل مارکف پنهان

Multi site modeling of rainfall is one of the most important issues in environmental sciences especially in watershed management. For this purpose, different statistical models have been developed which involve spatial approaches in simulation and modeling of daily rainfall values. The hidden Markov is one of the multi-site daily rainfall models which in addition to simulation of daily rainfall...