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 ...

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 ...

‡ Institute of Applied Physics, Center for Functional Nanostructures, and Institute of Toxicology and Genetics, Karlsruhe Institute of Technology (KIT), Wolfgang-Gaede-Str. 1, 76131 Karlsruhe, Germany ...

A complete C++ implementation of the Python hmmlearn library, featuring modern C++17, Eigen for linear algebra, and comprehensive HMM algorithms. hmm_c++/ ├── include/ # Header files │ ├── types.hpp # ...

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 ...

Sequentia is a Python package that provides various classification and regression algorithms for sequential data, including methods based on hidden Markov models and dynamic time warping. Some ...

The progression of complex diseases is generally divided as a normal state, a pre-disease state or tipping point, and a disease state. Developing individual-specific method that can identify the ...