Advanced

Robust Frequency-Selective Knowledge-Based Parameter Estimation for NMR Spectroscopy

Butt, Naveed LU ; Jakobsson, Andreas LU and Somasundaram, Samuel D. (2008) 16th European Signal Processing Conference.
Abstract
In many magnetic resonance spectroscopy (MRS)

applications, one strives to estimate the parameters

describing the signal to allow for more precise knowledge

of the analyte. Typically, MRS signals are well

modelled as a sum of damped sinusoids that has

properties that are partly known a priori. FREEK, a

recently proposed subspace-based parameter estimation

method allows for inclusion of such prior knowledge.

More specifically, FREEK assumes that there is a constant

frequency spacing (say Δ) between the damped

sinusoids, which is exactly known. However, any errors

in this prior knowledge will affect the accuracy of the

estimates.... (More)
In many magnetic resonance spectroscopy (MRS)

applications, one strives to estimate the parameters

describing the signal to allow for more precise knowledge

of the analyte. Typically, MRS signals are well

modelled as a sum of damped sinusoids that has

properties that are partly known a priori. FREEK, a

recently proposed subspace-based parameter estimation

method allows for inclusion of such prior knowledge.

More specifically, FREEK assumes that there is a constant

frequency spacing (say Δ) between the damped

sinusoids, which is exactly known. However, any errors

in this prior knowledge will affect the accuracy of the

estimates. Herein, we present an extension of FREEK,

making it robust to such errors by allowing Δ to lie

in a small interval and utilizing a robust estimate of

Δ in the estimation of the remaining parameters. The

proposed approach is numerically shown to provide

robust estimates of the sinusoidal parameters at various

noise levels in the presence of mismatch between the

actual and the assumed spacing. (Less)
Please use this url to cite or link to this publication:
author
publishing date
type
Contribution to conference
publication status
published
subject
conference name
16th European Signal Processing Conference.
external identifiers
  • Scopus:84863734024
language
English
LU publication?
no
id
deaa9149-5148-4218-ae48-45c4defaecc1 (old id 1232186)
alternative location
http://www.eurasip.org/Proceedings/Eusipco/Eusipco2008/papers/1569105068.pdf
date added to LUP
2009-05-28 11:09:13
date last changed
2017-01-01 08:13:49
@misc{deaa9149-5148-4218-ae48-45c4defaecc1,
  abstract     = {In many magnetic resonance spectroscopy (MRS)<br/><br>
applications, one strives to estimate the parameters<br/><br>
describing the signal to allow for more precise knowledge<br/><br>
of the analyte. Typically, MRS signals are well<br/><br>
modelled as a sum of damped sinusoids that has<br/><br>
properties that are partly known a priori. FREEK, a<br/><br>
recently proposed subspace-based parameter estimation<br/><br>
method allows for inclusion of such prior knowledge.<br/><br>
More specifically, FREEK assumes that there is a constant<br/><br>
frequency spacing (say Δ) between the damped<br/><br>
sinusoids, which is exactly known. However, any errors<br/><br>
in this prior knowledge will affect the accuracy of the<br/><br>
estimates. Herein, we present an extension of FREEK,<br/><br>
making it robust to such errors by allowing Δ to lie<br/><br>
in a small interval and utilizing a robust estimate of<br/><br>
Δ in the estimation of the remaining parameters. The<br/><br>
proposed approach is numerically shown to provide<br/><br>
robust estimates of the sinusoidal parameters at various<br/><br>
noise levels in the presence of mismatch between the<br/><br>
actual and the assumed spacing.},
  author       = {Butt, Naveed and Jakobsson, Andreas and Somasundaram, Samuel D.},
  language     = {eng},
  title        = {Robust Frequency-Selective Knowledge-Based Parameter Estimation for NMR Spectroscopy},
  year         = {2008},
}