[cig-commits] r19217 - seismo/3D/SPECFEM3D/trunk/doc/USER_MANUAL

[carltape at geodynamics.org]

Author: carltape
Date: 2011-11-18 14:31:26 -0800 (Fri, 18 Nov 2011)
New Revision: 19217

Modified:
   seismo/3D/SPECFEM3D/trunk/doc/USER_MANUAL/manual_SPECFEM3D.tex
Log:
updated citations in manual (Ch 11)


Modified: seismo/3D/SPECFEM3D/trunk/doc/USER_MANUAL/manual_SPECFEM3D.tex
===================================================================
--- seismo/3D/SPECFEM3D/trunk/doc/USER_MANUAL/manual_SPECFEM3D.tex	2011-11-18 21:50:33 UTC (rev 19216)
+++ seismo/3D/SPECFEM3D/trunk/doc/USER_MANUAL/manual_SPECFEM3D.tex	2011-11-18 22:31:26 UTC (rev 19217)
@@ -2450,7 +2450,7 @@
 
 One of the fundamental reasons for computing sensitivity kernels (Section~\ref{sec:Adjoint-simulation-finite}) is to use them within a tomographic inversion. In other words, use recorded seismograms, make measurements with synthetic seismograms, and use the misfit between the two to iteratively improve the model described by (at least) $V_{\rm p}$, $V_{\rm s}$, and $\rho$ as a function of space.
 
-Whatever misfit function you use for the tomographic inversion \citep[several examples in][]{Tromp2005}, you will weight the sensitivity kernels with measurements. Furthermore, you will use as many measurements (stations, components, time windows) as possible per event; hence, we call these composite kernels ``event kernels,'' which are volumetric fields representing the gradient of the misfit function with respect to one of the variables (\eg $V_{\rm s}$). The basic features of an adjoint-based tomographic inversion were illustrated in \citet{Tape2007} using a conjugate-gradient algorithm; there are dozens of versions of gradient-based inversion algorithms that could alternatively be used. The tomographic inversion of \citet{Tape2009,Tape2010} used SPECFEM3D as well as several additional components which are also stored on the CIG svn server, described next.
+Whatever misfit function you use for the tomographic inversion \citep[several examples in][]{TrTaLi05}, you will weight the sensitivity kernels with measurements. Furthermore, you will use as many measurements (stations, components, time windows) as possible per event; hence, we call these composite kernels ``event kernels,'' which are volumetric fields representing the gradient of the misfit function with respect to one of the variables (\eg $V_{\rm s}$). The basic features of an adjoint-based tomographic inversion were illustrated in \citet{TaLiTr07} using a conjugate-gradient algorithm; there are dozens of versions of gradient-based inversion algorithms that could alternatively be used. The tomographic inversion of \citet{TaLiMaTr09,TaLiMaTr2010} used SPECFEM3D as well as several additional components which are also stored on the CIG svn server, described next.
 
 The directory containing utilities for tomographic inversion using SPECFEM3D (or other packages that evaluate misfit functions and gradients) is here on the CIG svn server:
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