MODIFIED BAUM WELCH ALGORITHM ON HIDDEN MARKOV MODELS (Case Study: DNA sequences of Hylobates, Pongo, Gorilla, Homo sapiens, Pan)
In Hidden Markov Model (HMM), the estimation of parameter HMM (transition matrix, emission matrix, and prior probability) become interesting problem. The conventional Baum-Welch algorithm is a solution to resolve this issue. In fact, there are many high dimentional sequence of observations, such as...
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id-itb.:123052017-09-27T14:41:46ZMODIFIED BAUM WELCH ALGORITHM ON HIDDEN MARKOV MODELS (Case Study: DNA sequences of Hylobates, Pongo, Gorilla, Homo sapiens, Pan) PUSPITA S.R. (NIM 20108010), KARTIKA Indonesia Theses INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/12305 In Hidden Markov Model (HMM), the estimation of parameter HMM (transition matrix, emission matrix, and prior probability) become interesting problem. The conventional Baum-Welch algorithm is a solution to resolve this issue. In fact, there are many high dimentional sequence of observations, such as DNA sequences, that make estimation process take much time. Baum-Welch with modification with class specific, Gaussian Mixture Model, and Likelihood Ratio is considered to solve this problem. The observation sequences is classified by class specific. The Emission matrix is estimated using Gaussian Mixture Model. The Gaussian Mixture Model compounds by the hidden state and observation state. text |
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In Hidden Markov Model (HMM), the estimation of parameter HMM (transition matrix, emission matrix, and prior probability) become interesting problem. The conventional Baum-Welch algorithm is a solution to resolve this issue. In fact, there are many high dimentional sequence of observations, such as DNA sequences, that make estimation process take much time. Baum-Welch with modification with class specific, Gaussian Mixture Model, and Likelihood Ratio is considered to solve this problem. The observation sequences is classified by class specific. The Emission matrix is estimated using Gaussian Mixture Model. The Gaussian Mixture Model compounds by the hidden state and observation state. |
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Theses |
| author |
PUSPITA S.R. (NIM 20108010), KARTIKA |
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PUSPITA S.R. (NIM 20108010), KARTIKA MODIFIED BAUM WELCH ALGORITHM ON HIDDEN MARKOV MODELS (Case Study: DNA sequences of Hylobates, Pongo, Gorilla, Homo sapiens, Pan) |
| author_facet |
PUSPITA S.R. (NIM 20108010), KARTIKA |
| author_sort |
PUSPITA S.R. (NIM 20108010), KARTIKA |
| title |
MODIFIED BAUM WELCH ALGORITHM ON HIDDEN MARKOV MODELS (Case Study: DNA sequences of Hylobates, Pongo, Gorilla, Homo sapiens, Pan) |
| title_short |
MODIFIED BAUM WELCH ALGORITHM ON HIDDEN MARKOV MODELS (Case Study: DNA sequences of Hylobates, Pongo, Gorilla, Homo sapiens, Pan) |
| title_full |
MODIFIED BAUM WELCH ALGORITHM ON HIDDEN MARKOV MODELS (Case Study: DNA sequences of Hylobates, Pongo, Gorilla, Homo sapiens, Pan) |
| title_fullStr |
MODIFIED BAUM WELCH ALGORITHM ON HIDDEN MARKOV MODELS (Case Study: DNA sequences of Hylobates, Pongo, Gorilla, Homo sapiens, Pan) |
| title_full_unstemmed |
MODIFIED BAUM WELCH ALGORITHM ON HIDDEN MARKOV MODELS (Case Study: DNA sequences of Hylobates, Pongo, Gorilla, Homo sapiens, Pan) |
| title_sort |
modified baum welch algorithm on hidden markov models (case study: dna sequences of hylobates, pongo, gorilla, homo sapiens, pan) |
| url |
https://digilib.itb.ac.id/gdl/view/12305 |
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