Streaming prediction-error filters
Sergey B. Fomel, Jon F. Claerbout · 2016
Prediction-error filters (PEFs) play an important role in seismic deconvolution and other geophysical estimation problems. We show that non-stationary multidimensional PEFs can be computed in a “streaming” manner, where the filter gets updated incrementally by accepting one new data point at a time. The computational cost of computing a streaming PEF reduces to the cost of a single convolution. In other words, the cost of PEF design while filtering equals the cost of applying the filter. Moreover, the non-linear operation of finding and applying a streaming PEF is invertible at the same cost, which enables a fast approach to missing data interpolation. Presentation Date: Wednesday, October 19, 2016 Start Time: 9:15:00 AM Location: 148 Presentation Type: ORAL