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Title page for etd-0823104-170239


URN etd-0823104-170239 Statistics This thesis had been viewed 2162 times. Download 17 times.
Author Guan-Long Guo
Author's Email Address No Public.
Department Computer Science and Enginerring
Year 2003 Semester 2
Degree Master Type of Document Master's Thesis
Language English Page Count 85
Title A New Classification System of MIDI Music Files Based on Back Propagation Model
Keyword
  • Music Files
  • MIDI
  • Classification
  • Back Propagation
  • Back Propagation
  • Classification
  • MIDI
  • Music Files
  • Abstract The main purpose of this thesis is to investigate how to develop an effective classification system that can first categorize the characteristics in MIDI music files and then search similar music in the Internet. In this system, back propagation network is applied to train and categorize the characteristics in MIDI music. Many search engines now can provide efficient ways to search music. However, those search engines only search the files by the names of music, and cannot categorize and compare the music according to the characteristics of music. In this thesis, we select representative songs of eight specific music categories to construct a module that can identify the types of music by means of back propagation network. We introduce the theoretical basis of music classification and present the experiment results to validate the effectiveness of the proposed model.
    Advisor Committee
  • Yo-Ping Huang - advisor
  • Chia-Sheng Tsai - co-chair
  • Mao-Cheng Hong - co-chair
  • Yo-Ping Huang - co-chair
  • Files indicate in-campus access only
    Date of Defense 2004-07-09 Date of Submission 2004-08-23


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