• DocumentCode
    2676679
  • Title

    On the classification of compressed sensed signals

  • Author

    Fira, M. ; Goras, L. ; Cleju, N. ; Barabasa, C.

  • Author_Institution
    Inst. of Comput. Sci., Romanian Acad., Iaşi, Romania
  • fYear
    2011
  • fDate
    June 30 2011-July 1 2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper presents a study on the possibilities for the classification of ECG signals acquired based on the theory of compressed sensing (CS). We propose an analysis of the classification results of the ECG signals acquired according to Nyquist theorem as compared to compress sensed signals using two different classifiers, namely nearest neighbor type classifier and a MLP neural network.
  • Keywords
    electrocardiography; medical signal processing; neural nets; pattern classification; signal classification; signal reconstruction; ECG signal classification; MLP neural network; Nyquist theorem; compressed sense signal classification; nearest neighbor type classifier; Compressed sensing; Dictionaries; Electrocardiography; Matching pursuit algorithms; Pathology; Sparse matrices; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signals, Circuits and Systems (ISSCS), 2011 10th International Symposium on
  • Conference_Location
    lasi
  • Print_ISBN
    978-1-61284-944-7
  • Type

    conf

  • DOI
    10.1109/ISSCS.2011.5978769
  • Filename
    5978769
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2676679