By Schick T.

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**Example text**

53), which is uniquely solved due to rkŒGx C A0 AD m; jGx C A0 Aj ¤ 0. 48) and can be represented as follows. 3. (The minimum norm solution (MINOS) with respect to the Gx seminorm). e. A/, if and only if L 2 Rm n is represented by the following “relations”. AA0 / 1 Ax. AA0 / 1 Ax, I-MINOS has the reproducing property. AA0 / 1 A D n rkA D d are independent). AA0 / 1 Ax. AGx 1 A0 / 1 Ax/. AGx 1 A0 / 1 Ax, Gx -MINOS has the reproducing property. AGx 1 A0 / 1 A D n rkA D d are independent). AGx 1 A0 / 1 Ax.

Then the rank partitioning of xm is Gx -MINOS. 127). 128). 128) Proof. 58) and replace the matrix A 2 m by its canonical representation, namely eigenspace synthesis. 133) x2 0 0 0 The pair of eigensystems AA# L D Lƒ2 ; A# AR1 D R1 ƒ2 is unfortunately based upon non-symmetric matrices AA# D AGx 1 A0 Gy and A# A D Gx 1 A0 Gy A which make the left and right eigenspace analysis numerically more complex. It appears that we are forced to use the Arnoldi method rather than the more efficient Lanczos method used for symmetric matrices.

74). The forward reduction step 1-2 Minimum Norm Solution (MINOS) 21 is followed by the backward reduction step. 75). 76). 3. At first, we have to observe that the matrix Gx of the metric of the parameter space X has to be given a priori. We classified MINOS according to (i) Gx D Im , (ii) Gx positive-definite, and (iii) Gx positive semi-definite. But how do we know the metric of the parameters space? Obviously, we need prior information about the geometry of the parameter space X, namely from the empirical sciences like physics, chemistry, biology, geosciences, social sciences.