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

Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques

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)
Salami, M.J.E. ; Fac. of Eng., Int. Islamic Univ. Malaysia, Kuala Lumpur, Malaysia ; Ismail, Z.

Previous work has shown that the deconvolution technique is one of the most effective procedures for analyzing transient exponentially decaying signals. Direct deconvolution approach often leads to poor resolution of the estimated decay rates since the fast Fourier transform (FFT) algorithm is used to analyze the resulting deconvolved data. One of the most promising approaches is based on optimal inverse filtering followed by fitting an autoregressive moving average (ARMA) model to the deconvolved data so that its AR parameters are determined by solving high order Yule-Walker equations (HOYWE) via the singular value decomposition (SVD) algorithm. Many desirable results have been obtained by using this technique for both dean and noisy signals. However, the real-time implementation of this algorithm poses some difficulties since nonlinear transformation is involved in such analysis. One method of overcoming this difficulty is by incorporating the spline interpolation algorithm into the nonlinear preprocessing procedure. The performance of the proposed algorithm in accurately estimating the number of exponential signals and their corresponding exponential constants for both simulated and real data is investigated in this paper. Results of analysis have shown that high-resolution estimates of decay constants are obtained when the proposed algorithm is used to analyze multiexponential signals with varied signal-to-noise (SNR) ratio.

Published in:

Industrial Technology, 2003 IEEE International Conference on  (Volume:1 )

Date of Conference:

10-12 Dec. 2003

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.