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LINEAR OPTIMIZATION

Search algorithms usually have a common pitfall. The accuracy of its solution is limited to the increment at which the solution space is sampled, as is the algorithm described in the last section. One way to solve this problem is to reduce the sampling interval. However, doing this increases the size of the solution space, which, in turn, increases the computational cost substantially. I avoid this problem by estimating residual dips through a linear optimization.



 
previous up next print clean
Next: Residual dip Up: Zhang: Automatic picking Previous: Viterbi algorithm
Stanford Exploration Project
12/18/1997