Cart (Loading....) | Create Account
Close category search window
 

Several approaches to signal reconstruction from spectrum magnitudes

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

The purchase and pricing options are temporarily unavailable. Please try again later.
4 Author(s)
Burian, A. ; Tampere Univ. of Technol., Finland ; Saarinen, J. ; Kuosmanen, P. ; Rusu, C.

The problem of reconstructing a one-dimensional (1D) signal from only the magnitude of its Fourier transform emerges when the phase of a signal is apparently lost or impractical to measure. Previous solutions usually employed an iterative Fourier transform (IFT) algorithm applied on a discrete approximation of a signal. The utilization of these algorithms is seriously limited by the unpredictability of their convergence. We propose several solutions to the phase retrieval problem. The first two proposed solutions uses relationships between the phase and the gain differences (GD), or gain samples (GS), in nepers. The last proposed solution uses a neural network NN for solving the problem. The NN incorporates a combination of the maximum entropy estimation algorithm with some additional nonlinear constraints. We compare our solutions by using some numerical examples. The performances under noisy conditions are also considered

Published in:

Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on  (Volume:6 )

Date of Conference:

2001

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.