By Topic

Convergence analysis of a digital diffusion network

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

3 Author(s)
Yin, G. ; Dept. of Math., Wayne State Univ., Detroit, MI, USA ; Kelly, P.A. ; Gong, W.-B.

We propose a numerical procedure for approximating an analog diffusion network. The main idea, is to take advantage of the “separable” feature (of the noise) of the diffusion machine and use parallel processing method to develop recursive algorithms. In addition to the decreasing step size algorithm, constant step algorithms and procedures with periodic restarts are suggested. By means of weak convergence methods, the convergence of the algorithms is established. The algorithms may be useful for many large-scale optimization problems, including image segmentation

Published in:

Decision and Control, 1996., Proceedings of the 35th IEEE Conference on  (Volume:2 )

Date of Conference:

11-13 Dec 1996