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Arash Amini
Researcher at Sharif University of Technology
Publications - 139
Citations - 1922
Arash Amini is an academic researcher from Sharif University of Technology. The author has contributed to research in topics: Compressed sensing & Matrix (mathematics). The author has an hindex of 21, co-authored 116 publications receiving 1663 citations. Previous affiliations of Arash Amini include École Normale Supérieure & École Polytechnique Fédérale de Lausanne.
Papers
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Ultrasonics, Ferroelectrics, and Frequency Control
Craig Woody,Mos Kaveh,Michael Insana,M. Insana,E. Angelini,Y. K Im,A. B. Brill,R. Jaszczak,W. C Lem Karl,Milan Sonka,Honghai Zhang,Michael D. Abràmoff,Arash Amini,Stephen R. Aylward,C. Barillot,E. Bullitt,I. Buvat,D. Comaniciu,C. R. Crawford,James S. Duncan,J. A. Fessler,X. P. Hu,R. H. Huesman,M. F. Insana,P. I Rarrázaval,M. Jacob,T. Jiang,Nico Karssemeijer,E. A. Krupinski,P. Liang,Murray H. Loew,A. Manduca,Joseph M. Reinhardt,J. Sijbers,H. Soltanian-Zadeh,D. W. Townsend,Van Leemput,Moshe Kam,Gordon W. D Ay,Roger D. Pollard +39 more
Journal ArticleDOI
Deterministic Construction of Binary, Bipolar, and Ternary Compressed Sensing Matrices
Arash Amini,Farokh Marvasti +1 more
TL;DR: Due to the cyclic property of the BCH codes, the FFT algorithm can be employed in the reconstruction methods to considerably reduce the computational complexity.
Posted Content
Deterministic Construction of Binary, Bipolar and Ternary Compressed Sensing Matrices
Arash Amini,Farokh Marvasti +1 more
TL;DR: In this paper, the connection between the Orthogonal Optical Codes (OOC) and binary compressed sensing matrices was established and the RIP condition was established by means of coherence, and the simple greedy algorithms such as Matching Pursuit were able to recover the sparse solution from noiseless samples.
Posted Content
A Unified Approach to Sparse Signal Processing
Farokh Marvasti,Arash Amini,Farzan Haddadi,Mahdi Soltanolkotabi,Babak Hossein Khalaj,Akram Aldroubi,S. Holm,Saeid Sanei,Jonathon A. Chambers +8 more
TL;DR: A unified view of the area of sparse signal processing is presented in tutorial form by bringing together various fields in which the property of sparsity has been successfully exploited.
Journal ArticleDOI
A unified approach to sparse signal processing
Farokh Marvasti,Arash Amini,Farzan Haddadi,Mehdi Soltanolkotabi,Babak Hossein Khalaj,Akram Aldroubi,Saeid Sanei,Jonathon A. Chambers +7 more
TL;DR: In this article, a unified view of the area of sparse signal processing is presented in tutorial form by bringing together various fields in which the property of sparsity has been successfully exploited, including sampling, coding, spectral estimation, array processing, component analysis, and multipath channel estimation.