Downloadable Materials
- The slides for Margaret Cheney's presentations are here. (Scroll down to
Margaret Cheney, then Part 1 Presentation Slides (pdf), etc.) Three writeups for the radar labs are lab-fourier, lab-radar and lab-radar2.
- A fan-beam CT dataset is here. The
corresponding code to form an
image.
- Some handwritten notes for seismology can be downloaded from this course
website. (Scroll down to bibliographic references.) Some typeset notes were kindly provided by
Thibaut Lienart here and Nicholas Maxwell here. Here are the
slides for Felix Herrmann's lectures: slides 1 and slides 2. Here are the 2 files for the Marmousi model: marmousi.dat and marmousi_setup.m.
- From James Hall: the dataset P_hat that
you can load in Matlab for the linearized Marmousi example. The variables
are arranged as follows:
- omega - [1 x 128] Frequencies (128 evenly spaced frequencies
ranging from 96*pi to 160*pi)
- xdcr_loc - [2 x 128] Transducer (source/receiver) locations (these
are offset by -.25 to avoid near-field effects)
- xdcrInd - [384 x 2] Transducer pairs used for each event. s in the
first column and r in the second. Since we
used *3* sources (s = 1, 64, and 128)the row sequence will look like
(1,1), (1,2), (1,3) ... (64,1), (64,2) ...
(128,127), (128,128).
- xx,yy - [128 x 128] x- and y- coordinates
- G(omega,d) - Function that provides G_hat value as a function of
frequency (omega) and propagation distance (d)
- P_hat - [384 x 128] Data set values arranged with transducer
pairs in
each row (corresponding to xdcrInd) and
frequencies in the columns (corresponding to omega).
Please note that no Ricker wavelet was applied in this example. It is fine
to ignore the wavelet issue at first.
- Notes for random media and passive imaging: intro probability, slides 1, slides 2. Labs for random media
and passive imaging: labs days 1 and 2, lab day 3, lab day 4.
- The event poster in US letter and A4 formats.
