List of Articles Hidden Markov Model (HMM)

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  1 - A New Approach to Overcome the Count to Infinity Problem in DVR Protocol Based on HMM Modelling
  Mehdi Golestanian Reza Ghazizadeh
  10.7508/jist.2013.04.007
  Due to low complexity, power and bandwidth saving Distance Vector Routing has been introduced as one of the most popular dynamic routing protocol. However, this protocol has a serious drawback in practice called Count To Infinity problem or slow convergence. There are m More

  Due to low complexity, power and bandwidth saving Distance Vector Routing has been introduced as one of the most popular dynamic routing protocol. However, this protocol has a serious drawback in practice called Count To Infinity problem or slow convergence. There are many proposed solutions in the literature to solve the problem, but all of these methods depend on the network topology, and impose much computational complexity to the network. In this paper, we introduce a new approach to solve the Count To Infinity using hidden markov model (HMM), which is one of the most important machine learning tools. As the modelling results show, the proposed method is completely independent from the network topology and simple with low computational complexity. Manuscript profile
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  2 - Persian Handwritten Word Recognition by Log-Polar Transform and Hidden Markov Model
  Q. Nadalinia Charei K. Yaghmaie H. Fazlollahi Aghamalek S. M. Razavi
  In this paper a recognition system for Persian words is introduced which utilizes the local higher order of the log-polar image autocorrelation for feature extraction of Persian sub-words. This feature extraction technique brings up leads to a system robustness in cases More

  In this paper a recognition system for Persian words is introduced which utilizes the local higher order of the log-polar image autocorrelation for feature extraction of Persian sub-words. This feature extraction technique brings up leads to a system robustness in cases of writing variations alteration like scaled or rotated handwritings. Also using the log-polar transform, the sub-word image sampling will be performed so that most of acquired samples will be centered in a certain area. The proposed method uses the discrete Hidden Markov’s Model (HMM) as a classifier. Furthermore a net of dictionaries were employed to increase the reliability and precision of the system output. Finally, the Iran-Shahr database is utilized to evaluate the system performance. Comparing the results of the proposed method and other previous methods, proves that a less sensitivity has been achieved by the proposed method about handwriting variations. Manuscript profile