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PSG Data Compression And Decompression Based On Compressed Sensing

ChangHyun, Lee

Abstract Details

2011, Master of Sciences (Engineering), Case Western Reserve University, EECS - System and Control Engineering.
In the thesis, the compression and decompression scheme based on Compressive Sensing (CS) is developed for multichannel polysomnography(PSG) data. This thesis is composed of three main parts: (i) The signals in all channels are first classified according to their possible sparse representations. (ii) The two different compression and decompression methods applicable to batch and sequential measurements are implemented for each kind of signals, respectively. (iii) We present the optimal compression and decompression scheme based on batch and sequential measurements, and the results which is included compression ratio, accuracy, compression and decompression time are showed and compared to save much more storage space in the database.
Guo-Qiang Zhang, PhD (Advisor)
Rong Xu, PhD (Committee Member)
Vira Chankong, PhD (Committee Member)
174 p.

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Citations

  • ChangHyun, L. (2011). PSG Data Compression And Decompression Based On Compressed Sensing [Master's thesis, Case Western Reserve University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=case1310065394

    APA Style (7th edition)

  • ChangHyun, Lee. PSG Data Compression And Decompression Based On Compressed Sensing. 2011. Case Western Reserve University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=case1310065394.

    MLA Style (8th edition)

  • ChangHyun, Lee. "PSG Data Compression And Decompression Based On Compressed Sensing." Master's thesis, Case Western Reserve University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=case1310065394

    Chicago Manual of Style (17th edition)