Inverse Theory and Data Interpretation

Description: Lecture, three hours. Requisites: Mathematics 115A, 170A, 170B, 171. Inverse modeling problem--determination of model parameters consistent with experimental data, considering effects of random errors and nonuniqueness. Emphasis on linear and quasi-linear problems; nonlinear problems also discussed. Tools used include matrix theory, quadratic forms, orthogonal rotations, statistics, principal axis transformation for rectangular matrices, Bachus/Gilbert resolving kernels, and Lagrange multipliers. Examples from broad range of physical sciences. S/U or letter grading.

Units: 4.0
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