@article{discovery10061831,
           month = {November},
          number = {11},
       publisher = {APPLIED COMPUTATIONAL ELECTROMAGNETICS SOC},
           title = {Fast Monostatic Scattering Analysis Based on Bayesian Compressive Sensing},
            year = {2016},
         journal = {Applied Computational Electromagnetics Society Journal},
          volume = {31},
            note = {This version is the version of record. For information on re-use, please refer to the publisher's terms and conditions.},
           pages = {1279--1285},
             url = {http://www.aces-society.org/journal.php},
            issn = {1943-5711},
        abstract = {The Bayesian compressive sensing algorithm
is utilized together with the method of moments to
fast analyze the monostatic electromagnetic scattering
problem. Different from the traditional compressive
sensing based fast monostatic scattering analysis method
which cannot determine the required measurement times,
the proposed method adopts the Bayesian framework
to recover the underlying signal. Error bars of the signal
can be obtained in the recovery procedure, which
provides a means to adaptively determine the number of
compressive-sensing measurements. Numerical results
are given to demonstrate the accuracy and effectiveness
of proposed method.},
          author = {Zhang, H-H and Zhao, X-W and Lin, Z-C and Sha, WEI},
        keywords = {Science \& Technology, Technology, Engineering, Electrical \& Electronic, Telecommunications, Engineering, Bayesian compressive sensing, method of moments, monostatic, scattering, FAST-MULTIPOLE ALGORITHM, ELECTROMAGNETIC SCATTERING, INTEGRAL-EQUATIONS, MOMENTS, SOLVER}
}