Nazanin Asadi

  • Citations Per Year
Learn More
Hidden Markov Model (HMM) is a widespread statistical model used in cases where the system involves not fully observable data sequences such as temporal pattern recognition and signal processing. The most difficult problem in dealing with HMMs is the training procedure, or parameter learning, for which several approaches has been proposed. Nevertheless,(More)
Classification of temporal data sequences is a fundamental branch of machine learning with a broad range of real world applications. Since the dimensionality of temporal data is significantly larger than static data, and its modeling and interpreting is more complicated, performing classification and clustering on temporal data is more complex as well.(More)
  • 1