Abstract: We consider system identification (learning) problems for Gaussian hidden Markov models (GHMMs). We propose an algorithm to tackle the cases where the data is recorded in aggregate ...

Abstract: Existing algorithms for estimating the model parameters of an explicit-duration hidden Markov model (HMM) usually require computations as large as O((MD/sup 2/ + M/sup 2/)T) or O(M/sup 2/ DT ...

Graphical representations model complex networks by encoding entities as vertices and interactions as edges, with recurring subgraphs—or motifs—revealing fundamental organizational principles. We ...

Mathematics often seems like an abstract concept, but its applications can have profound impacts on the world around us. From predicting the next word in a sentence to understanding how Google’s ...

This paper presents the application of the unscented Kalman filter (UKF) for estimating the dynamic states of a maneuvering tank using a second-order Gauss-Markov process model. The proposed method is ...

Individuals in the midst of a mental health crisis frequently exhibit instability and face an elevated risk of recurring crises in the subsequent weeks, which underscores the importance of timely ...

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Markov chains are an essential component of stochastic systems. They are frequently used in a variety of areas. A Markov chain is a stochastic process that meets the Markov property, which states that ...

After two decades at the center of college football's most notorious ranking system, the creators of the arcane computer polls that accounted for one-third of the BCS formula look back on the clashes ...