# Signal reconstruction from given phase of the Fourier transform using Fejér monotone methods

• Volume: 20, Issue: 1, page 27-40
• ISSN: 1509-9407

top

## Abstract

top
The aim is to reconstruct a signal function x ∈ L₂ if the phase of the Fourier transform [x̂] and some additional a-priori information of convex type are known. The problem can be described as a convex feasibility problem. We solve this problem by different Fejér monotone iterative methods comparing the results and discussing the choice of relaxation parameters. Since the a-priori information is partly related to the spectral space the Fourier transform and its inverse have to be applied in each iterative step numerically realized by FFT techniques. The computation uses MATLAB routines.

## How to cite

top

Dieter Schott. "Signal reconstruction from given phase of the Fourier transform using Fejér monotone methods." Discussiones Mathematicae, Differential Inclusions, Control and Optimization 20.1 (2000): 27-40. <http://eudml.org/doc/271532>.

@article{DieterSchott2000,
abstract = {The aim is to reconstruct a signal function x ∈ L₂ if the phase of the Fourier transform [x̂] and some additional a-priori information of convex type are known. The problem can be described as a convex feasibility problem. We solve this problem by different Fejér monotone iterative methods comparing the results and discussing the choice of relaxation parameters. Since the a-priori information is partly related to the spectral space the Fourier transform and its inverse have to be applied in each iterative step numerically realized by FFT techniques. The computation uses MATLAB routines.},
author = {Dieter Schott},
journal = {Discussiones Mathematicae, Differential Inclusions, Control and Optimization},
keywords = {signal reconstruction; convex feasibility problem; projection onto convex sets; Fejér monotone iterative methods; Fourier transforms; convex feasibility; Fourier transform},
language = {eng},
number = {1},
pages = {27-40},
title = {Signal reconstruction from given phase of the Fourier transform using Fejér monotone methods},
url = {http://eudml.org/doc/271532},
volume = {20},
year = {2000},
}

TY - JOUR
AU - Dieter Schott
TI - Signal reconstruction from given phase of the Fourier transform using Fejér monotone methods
JO - Discussiones Mathematicae, Differential Inclusions, Control and Optimization
PY - 2000
VL - 20
IS - 1
SP - 27
EP - 40
AB - The aim is to reconstruct a signal function x ∈ L₂ if the phase of the Fourier transform [x̂] and some additional a-priori information of convex type are known. The problem can be described as a convex feasibility problem. We solve this problem by different Fejér monotone iterative methods comparing the results and discussing the choice of relaxation parameters. Since the a-priori information is partly related to the spectral space the Fourier transform and its inverse have to be applied in each iterative step numerically realized by FFT techniques. The computation uses MATLAB routines.
LA - eng
KW - signal reconstruction; convex feasibility problem; projection onto convex sets; Fejér monotone iterative methods; Fourier transforms; convex feasibility; Fourier transform
UR - http://eudml.org/doc/271532
ER -

## References

top
1. [1] H.H. Bauschke and J.M. Borwein, On projection algorithms for solving convex feasibility problems, SIAM Rev. 38 (1996), 367-426. Zbl0865.47039
2. [2] P.L. Combettes, Fejér-monotonicity in convex optimization, in: C.A. Floudas and P.M. Pardalos (eds.), Encyclopedia of Optimization, Kluwer Acad. Publ., Dordrecht 2000.
3. [3] L.G. Gubin, B.T. Polyak and E.V. Raik, The method of projections for finding the common point of convex sets, USSR Comput. Math. Math. Phys. 7 (1967), 1-24.
4. [4] M.H. Hayes, J.S. Lim and A.V. Oppenheim, Signal reconstruction from phase or magnitude, IEEE Trans. Acoust. Speech and Signal Process. ASSP-28 (1980), 672-680. Zbl0521.94004
5. [5] M.H. Hayes, The reconstruction of a multidimensional sequence from the phase or magnitude of its Fourier transform, IEEE Trans. Acoust. Speech and Signal Process. ASSP-30 (1982), 140-154. Zbl0563.65084
6. [6] A. Levi and H. Stark, Restoration from Phase and Magnitude by Generalized Projections, in: [] , Chapter 8, 277-320.
7. [7] D. Schott, Iterative solution of convex problems by Fejér monotone methods, Numer. Funct. Anal. Optimiz. 16 (1995), 1323-1357. Zbl0853.65055
8. [8] D. Schott, Basic properties of Fejér monotone mappings, Rostock. Math. Kolloq. 50 (1997), 71-84. Zbl0905.65068
9. [9] D. Schott, Weak convergence of iterative methods generated by strongly Fejér monotone methods, Rostock. Math. Kolloq. 51 (1997), 83-96. Zbl0890.65055
10. [10] D. Schott, About strongly Fejér monotone mappings and their relaxations, Zeitschr. Anal. Anw. 16 (1997), 709-726. Zbl0882.65043
11. [11] H. Stark (ed.), Image recovery: Theory and applications, Academic Press, New York 1987.
12. [12] D.C. Youla, Mathematical Theory of Image Restoration by the Method of Convex Projections, in: [11], Chapter 2, 29-76.

## NotesEmbed?

top

You must be logged in to post comments.

To embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.

Only the controls for the widget will be shown in your chosen language. Notes will be shown in their authored language.

Tells the widget how many notes to show per page. You can cycle through additional notes using the next and previous controls.

Note: Best practice suggests putting the JavaScript code just before the closing </body> tag.