Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...

Abstract: This paper considers angle-of-arrival (AOA) target tracking in the two-dimensional plane with non-Gaussian noise. Practical situations arise where sensor measurement noise is non-Gaussian ...

Building a utility-scale quantum computer that can crack one of the most vital cryptosystems—elliptic curves—doesn’t require nearly the resources anticipated just a year or two ago, two independently ...

This package contains functions implementing the BrainMap model proposed in Mejia et al. (2019) and the spatial BrainMap model proposed in proposed in Mejia et al. (2020+). (Previously, these models ...

Abstract: Direction-of-arrival (DOA) estimation for wideband source signals using far-field acoustic sensors has recently drawn much research interest. A wide variety of DOA estimation approaches are ...

In recent years, a learning method for classifiers using tensor networks (TNs) has attracted attention. When constructing a classification function for high-dimensional data using a basis function ...

This paper shows that the Expectation-Maximization (EM) algorithm for regime-switching dynamic factor models provides satisfactory performance relative to other estimation methods and delivers a good ...

ABSTRACT: This paper is concerned about studying modeling-based methods in cluster analysis to classify data elements into clusters and thus dealing with time series in view of this classification to ...

Planar motion constraint occurs in visual odometry (VO) and SLAM for Automated Guided Vehicles (AGVs) or mobile robots in general. Conventionally, two-point solvers can be nested to RANdom SAmple ...

Various Expectation-Maximization (EM) algorithms are implemented for item response theory (IRT) models. The current implementation includes IRT models for binary and ordinal responses, along with ...