An analysis of the influence of missing samples in signals exhibiting sparsity in the Hermite transform domain is presented. Based on the statistical properties derived for the Hermite coefficients of randomly undersampled signal, the probability of success in detection of signal components support is determined and a threshold for the detection of signal components is provided. It is a crucial step in a simple noniterative and iterative matching pursuit (MP)-based algorithm for compressive sensing signal reconstruction.


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    Title :

    Compressive Sensing of Sparse Signals in the Hermite Transform Basis


    Contributors:


    Publication date :

    2018-04-01


    Size :

    1582084 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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