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2. Principles of some measurement inversion methods
2.1 Parameterization and dispersion bias trade-offs
2.1.1 Effects of parameter vector size
We now turn to the special case of estimating a function x (t ) from m measurements collected in a vectory (m here represents the number of data points, i.e. the product of the number of sensors and the number of acquisition time steps). This problem is always ill-posed, as any function can be considered as a vector with an infinite number of independent coefficients, i.e. an infinite number of degrees of freedom....
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Principles of some measurement inversion methods
Inverse methods and commercial software
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