DocumentCode :
164418
Title :
Phase retrieval of sparse L-ary signals from magnitudes of their Fourier transform
Author :
Borujeni, Mohsen Shabanian ; Parvaresh, Farzad
Author_Institution :
Dept. of Electr. Eng., Univ. of Isfahan, Isfahan, Iran
fYear :
2014
fDate :
7-8 May 2014
Firstpage :
1
Lastpage :
5
Abstract :
The problem of recovering a sparse L-ary signal from magnitudes of its Fourier transform or equivalently its autocorrelation function is considered. Although, one can show that solving the phase retrieval problem for L-ary signals is possible in time that is polynomial in L and length of the signal, however, the current algorithms are still not practical. We introduce a backtracking algorithm on a tree which solves the phase retrieval problem. By simulations, we show that the average number of nodes visited on the tree by the backtracking algorithm grows polynomially in L and signal length, although the search tree has an exponential size.
Keywords :
Fourier transforms; correlation methods; polynomials; signal processing; trees (mathematics); Fourier transform; autocorrelation function; backtracking algorithm; exponential size; search tree; signal length; sparse L-ary signal phase retrieval problem; Approximation algorithms; Correlation; Fourier transforms; Mathematical model; Optimization; Polynomials;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communication and Information Theory (IWCIT), 2014 Iran Workshop on
Conference_Location :
Tehran
Print_ISBN :
978-1-4799-4878-9
Type :
conf
DOI :
10.1109/IWCIT.2014.6842506
Filename :
6842506
Link To Document :
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