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As the most important part in living creature’s growth, DNA provides an interesting problem to investigated. In the research, DNA can be representated as a random variable which has a stochastic process, especially Markov chain because the variable is a discrete variable. It is insufficient to so...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/16300 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | As the most important part in living creature’s growth, DNA provides an interesting problem to investigated. In the research, DNA can be representated as a random variable which has a stochastic process, especially Markov chain because the variable is a discrete variable. It is insufficient to solve this problem using a simple Markov Chain, therefore the chain is expanded into a Hidden Markov Model. Viterbi Algorithm is an algorithm which uses the model to find the hidden state sequence which constructs the DNA and follow as a Markov chain. Until now, Viterbi Algorithm is believed as the best solution to find the hidden state sequence of an observation sequence. This algorithm’s flaw is, when tracking the hidden state sequence using Hidden Markov Model, it is not possible <br />
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to find the history of its hidden state sequence. Entropy as an uncertainty standard can be used to find the history better than Viterbi Algorithm. |
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