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

An analytical approach to signal reconstruction using Gaussian approximations applied to randomly generated and flow cytometric data

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

4 Author(s)
Adjouadi, M. ; Dept. of Electr. & Comput. Eng., Florida Int. Univ., Miami, FL, USA ; Reyes, C. ; Vidal, P. ; Barreto, A.B.

This study introduces an analytical approach to signal reconstruction using Gaussian distributions. A major problem encountered in real-world data distributions is in the ability to accurately separate those data distributions that experience overlap. A first objective then is to develop a method of determining accurately the characteristics of a given distribution even when it has been affected by another distribution that lies close to it. In addition, normally, two-dimensional (2-D) Gaussian distributions are described by means of a correlation coefficient, but in this case, a normal 2-D distribution will be assumed in a direction parallel to a reference axis and then rotated by some angle θ. This outcome will not affect the results in terms of the standard use of the correlation coefficient. In this study, an attempt is made to provide a highly accurate yet computationally inexpensive approach of resolving the problem of overlap as we seek the reconstruction of signals through Gaussian curve fitting. Implementation results are shown in support of this assertion

Published in:

Signal Processing, IEEE Transactions on  (Volume:48 ,  Issue: 10 )

Date of Publication:

Oct 2000

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.