Scheduled System Maintenance:
Some services will be unavailable Sunday, March 29th through Monday, March 30th. We apologize for the inconvenience.
By Topic

A recurrent neural network for 1-D phase retrieval

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.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Burian, A. ; Inst. of Digital & Comput. Syst., Tampere Univ. of Technol., Finland ; Takala, J.

In this paper we propose the use of recurrent neural networks for solving the problem of signal restoration from its Fourier spectrum magnitudes. The neural network incorporates the constants related to the real and imaginary parts of the spectrum. We analyze the stability and convergence of the proposed neural network. The solution is provided by the steady state of the neural network. The obtained simulation results demonstrate the high efficiency of our approach.

Published in:

Circuits and Systems, 2003. ISCAS '03. Proceedings of the 2003 International Symposium on  (Volume:5 )

Date of Conference:

25-28 May 2003