Title :
1-D and 2-D minimum and non-minimum phase retrieval by solving linear systems of equations
Author :
Yagle, Andrew E.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
Abstract :
The discrete phase retrieval problem is to reconstruct a discrete-time signal whose support is known and compact from the magnitude of its discrete Fourier transform. We assume knowledge of some values of the signal, e.g. bands of zeros or known values, and solve the problem by solving linear systems of equations. No rooting of polynomials or tracking zero curves of algebraic functions (both very expensive computationally and unstable numerically) is required. Not only is our method much simpler computationally than previous methods, but it also allows the use of total least squares type techniques to be applied to the linear systems of equations, so that noisy data can be handled
Keywords :
discrete Fourier transforms; discrete time systems; least squares approximations; linear algebra; signal reconstruction; 1D minimum phase retrieval; 1D nonminimum phase retrieval; 1D signal; 2D minimum phase retrieval; 2D nonminimum phase retrieval; 2D signal; DFT; compact signal support; discrete Fourier transform magnitude; discrete phase retrieval; discrete-time signal reconstruction; linear equations; noisy data; total least squares; Discrete Fourier transforms; Discrete transforms; Ear; Equations; Fourier transforms; Image reconstruction; Iterative algorithms; Least squares methods; Linear systems; Polynomials;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-3192-3
DOI :
10.1109/ICASSP.1996.544132