Behavior Detection Using Confidence Intervals of Hidden Markov Models

@article{Brooks2009BehaviorDU,
  title={Behavior Detection Using Confidence Intervals of Hidden Markov Models},
  author={Richard R. Brooks and Jason M. Schwier and Christopher Griffin},
  journal={IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)},
  year={2009},
  volume={39},
  pages={1484-1492}
}
Markov models are commonly used to analyze real-world problems. Their combination of discrete states and stochastic transitions is suited to applications with deterministic and stochastic components. Hidden Markov models (HMMs) are a class of Markov models commonly used in pattern recognition. Currently, HMMs recognize patterns using a maximum-likelihood approach. One major drawback with this approach is that data observations are mapped to HMMs without considering the number of data samples… CONTINUE READING
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