We present a new method for nonlinear prediction of discrete random sequences under minimal structural assumptions. We give a mathematical construction for optimal predictors of s...
Background: Profile Hidden Markov Models (HMM) are statistical representations of protein families derived from patterns of sequence conservation in multiple alignments and have b...
Prashant K. Srivastava, Dhwani K. Desai, Soumyadee...
The analysis of facial expression temporal dynamics is of great importance for many real-world applications. Being able to automatically analyse facial muscle actions (Action Units...
Hidden Markov models assume that observations in time series data stem from some hidden process that can be compactly represented as a Markov chain. We generalize this model by as...
Abstract. Missing data in corrupted audio recordings poses a challenging problem for audio signal processing. In this paper we present an approach that allows us to estimate missin...