• English
    • العربية
  • العربية
  • Login
  • QU
  • QU Library
  •  Home
  • Communities & Collections
  • Help
    • Item Submission
    • Publisher policies
    • User guides
    • FAQs
  • About QSpace
    • Vision & Mission
View Item 
  •   Qatar University Digital Hub
  • Qatar University Institutional Repository
  • Academic
  • Faculty Contributions
  • College of Engineering
  • Electrical Engineering
  • View Item
  • Qatar University Digital Hub
  • Qatar University Institutional Repository
  • Academic
  • Faculty Contributions
  • College of Engineering
  • Electrical Engineering
  • View Item
  •      
  •  
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Calibration of time features and frequency features in the time-frequency domain for improved detection and classification of seizure in newborn EEG signals

    Thumbnail
    Date
    2012
    Author
    Bahnasy Y.
    Saad N.
    Boubchir L.
    Boashash B.
    Metadata
    Show full item record
    Abstract
    This paper presents new time-frequency features for seizure detection in newborn EEG signals. These features are obtained by calibrating relevant time features and frequency features in the joint time-frequency domain. The proposed features allow the possibility of improving the performance of the seizure detection and classification system based on multi-class SVM classifier.
    DOI/handle
    http://dx.doi.org/10.1109/ISSPA.2012.6310531
    http://hdl.handle.net/10576/31939
    Collections
    • Electrical Engineering [‎2821‎ items ]

    entitlement

    Related items

    Showing items related by title, author, creator and subject.

    • Thumbnail

      Time-frequency signal and image processing of non-stationary signals with application to the classification of newborn EEG abnormalities 

      Boashash, Boualem; Boubchir, Larbi; Azemi, Ghasem ( IEEE , 2011 , Conference)
      This paper presents an introduction to time-frequency (T-F) methods in signal processing, and a novel approach for EEG abnormalities detection and classification based on a combination of signal related features and image ...
    • Thumbnail

      Time-frequency features for pattern recognition using high-resolution TFDs: A tutorial review 

      Boashash B.; Khan N.A.; Ben-Jabeur T. ( Elsevier Inc. , 2015 , Article)
      This paper presents a tutorial review of recent advances in the field of time-frequency (t, f) signal processing with focus on exploiting (t, f) image feature information using pattern recognition techniques for detection ...
    • Thumbnail

      Estimating the number of components of a multicomponent nonstationary signal using the short-term time-frequency Rényi entropy 

      Sucic, Victor; Saulig, Nicoletta; Boashash, Boualem ( Springer , 2011 , Article)
      The time-frequency Rényi entropy provides a measure of complexity of a nonstationary multicomponent signal in the time-frequency plane. When the complexity of a signal corresponds to the number of its components, then this ...

    Qatar University Digital Hub is a digital collection operated and maintained by the Qatar University Library and supported by the ITS department

    Contact Us | Send Feedback
    Contact Us | Send Feedback | QU

     

     

    Home

    Submit your QU affiliated work

    Browse

    All of Digital Hub
      Communities & Collections Publication Date Author Title Subject Type Language Publisher
    This Collection
      Publication Date Author Title Subject Type Language Publisher

    My Account

    Login

    Statistics

    View Usage Statistics

    About QSpace

    Vision & Mission

    Help

    Item Submission Publisher policiesUser guides FAQs

    Qatar University Digital Hub is a digital collection operated and maintained by the Qatar University Library and supported by the ITS department

    Contact Us | Send Feedback
    Contact Us | Send Feedback | QU

     

     

    Video