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Two observations are exploited for this estimation.
For this estimation, interest points should be detected and described.
Because the fault parameters are needed for this estimation, the number of available earthquakes was limited.
We also provide the Cramér-Rao bound for this estimation problem.
We used the baytap08 software (Tamura et al., 1991; Tamura and Agnew, 2008) for this estimation.
The input data for this estimation are the identified clusters from a measurement route.
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We discuss the actual experiment for developing this estimation algorithm in the Experimental results section.
This means that the computer codes developed for this empirical estimation worked on right estimation track.
For noisy environments, this estimation can be improved by using a GPS.
Let Di represent this estimation, for the tap completing the interval Ii, and A*i the corresponding perceived asynchrony.
One of methods for this dual estimation is to use EKF by taking the parameters as additional states and augmenting state equations [39].
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