#TITLE_ALTERNATIVE#
The Application of Hidden Markov Model (HMM) had known especially in technical field. Along with the time HMM also growth in Biotechnology field, particularly in studying DNA behaviour where the DNA structure already well systemized. There are 3 main problem on HMM that is, 1. Counting observation p...
Saved in:
| Main Author: | |
|---|---|
| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/10756 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| id |
id-itb.:10756 |
|---|---|
| spelling |
id-itb.:107562017-09-27T11:43:05Z#TITLE_ALTERNATIVE# PUSPITA SARI RACHMAWATI (NIM 10104097), KARTIKA Indonesia Final Project INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/10756 The Application of Hidden Markov Model (HMM) had known especially in technical field. Along with the time HMM also growth in Biotechnology field, particularly in studying DNA behaviour where the DNA structure already well systemized. There are 3 main problem on HMM that is, 1. Counting observation probability if given λ model (transition matrix (A), emission matrix (B), and initial probability (π0)), 2. deciding optimal condition of hidden sequences, 3. adjust λ model that maximize the probability value on first problem. Often the model isn't known by the researcher. Eventually the first initial value is recited again to solve the first and the second problem. The solution of the first problem use forward algorithm and backward algorithm, and solution for the second problem using the Viterbi algorithm. The meaning of reciting initial value influence is by looking at rate of the next step convergence from both algorithms. text |
| institution |
Institut Teknologi Bandung |
| building |
Institut Teknologi Bandung Library |
| continent |
Asia |
| country |
Indonesia Indonesia |
| content_provider |
Institut Teknologi Bandung |
| collection |
Digital ITB |
| language |
Indonesia |
| description |
The Application of Hidden Markov Model (HMM) had known especially in technical field. Along with the time HMM also growth in Biotechnology field, particularly in studying DNA behaviour where the DNA structure already well systemized. There are 3 main problem on HMM that is, 1. Counting observation probability if given λ model (transition matrix (A), emission matrix (B), and initial probability (π0)), 2. deciding optimal condition of hidden sequences, 3. adjust λ model that maximize the probability value on first problem. Often the model isn't known by the researcher. Eventually the first initial value is recited again to solve the first and the second problem. The solution of the first problem use forward algorithm and backward algorithm, and solution for the second problem using the Viterbi algorithm. The meaning of reciting initial value influence is by looking at rate of the next step convergence from both algorithms. |
| format |
Final Project |
| author |
PUSPITA SARI RACHMAWATI (NIM 10104097), KARTIKA |
| spellingShingle |
PUSPITA SARI RACHMAWATI (NIM 10104097), KARTIKA #TITLE_ALTERNATIVE# |
| author_facet |
PUSPITA SARI RACHMAWATI (NIM 10104097), KARTIKA |
| author_sort |
PUSPITA SARI RACHMAWATI (NIM 10104097), KARTIKA |
| title |
#TITLE_ALTERNATIVE# |
| title_short |
#TITLE_ALTERNATIVE# |
| title_full |
#TITLE_ALTERNATIVE# |
| title_fullStr |
#TITLE_ALTERNATIVE# |
| title_full_unstemmed |
#TITLE_ALTERNATIVE# |
| title_sort |
#title_alternative# |
| url |
https://digilib.itb.ac.id/gdl/view/10756 |
| _version_ |
1820665952883179520 |