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Our method essentially updates two blocks of variables in turn by inexactly minimizing this potential function, and updates another auxiliary block of variables using an explicit formula.

The special structure of our potential function allows us to take advantage of efficient computational strategies for non-negative matrix factorization to perform the alternating minimization over the two blocks of variables.

I ran into an issue where some cells weren't calculating.

The CLM method is also sensitivity-based and uses a population of search points, which are subjected to constraints that enforce them to end in the same minimum.What I found to be the problem was the formula and the fact that I surrounded numbers with quotes.That probably turned the cell into a text format cell, even though technically the cell was still a number and listed as one under the formats.Generally, the discrepancies in eigenfrequencies and mode shapes are minimized, but also the discrepancies in modal strains can be included.Damage functions are used to approximate the stiffness distribution, as an efficient approach to reduce the number of unknowns. The Gauss-Newton method is a standard sensitivity-based method for local optimization of least squares problems and is ameliorated here by implementing it with the trust region strategy.Ctrl F9 not only updated the values, but fixed the problem so it didn't happen again.