• 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.