Background: The importance of stochasticity in cellular processes having low number of molecules has resulted in the development of stochastic models such as chemical master equat...
First-order Markov models have been successfully applied to many problems, for example in modeling sequential data using Markov chains, and modeling control problems using the Mar...
This paper presents a Bayesian approach for Gaussian mixture model (GMM)-based speaker identification. Some approaches evaluate the speaker score of a test speech utterance using ...
Abstract. This paper deals with maximum likelihood and least square segmentation of autoregressive random sequences with abruptly changing parameters. Conditional distribution of t...
The choice of the best-suited statistical distribution for modeling data is not a trivial issue. Unless a sound theoretical background exists for selecting a particular distributi...