The amino acid sequence of the transmembrane protein and its corresponding positions on the cell membrane are transformed into a hidden Markov process. After evaluating the parameters, the Viterbi ...

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 # ...

The EM algorithm is based on Yu (2010) (Section 3.1, 2.2.1 & 2.2.2), while the Viterbi algorithm is based on Benouareth et al. (2008).

Machine learning is the study of intelligent machines that can learn from data and anticipate future outcomes. One of the most important components of machine learning is dealing with uncertainty, ...

Abstract: We present an approach for a physics-informed Hidden Markov Model with a special emphasis on including prior physical knowledge in the Viterbi algorithm. To this end, we develop a ...

A Hidden Markov Model (HMM) is a statistical model which is also used in machine learning. It can be used to describe the evolution of observable events that depend on internal factors, which are not ...

With the popularity of new energy grids with high penetration rate, classic non-intrusive power load identification algorithms such as hidden Markov model (HMM) need to face the uncertainty caused by ...