Weird Sum of Squares as a Vector Norm and Gauss-Newton optimization

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SUMMARY

The discussion centers on the mathematical representation of the sum of squares as a vector norm in the context of Gauss-Newton optimization. Specifically, it addresses the function C(x) = || (F , 0) + (T , K).Z.x ||², where F is a constant, T is a 1×2 matrix, and K is a 3×3 matrix. The confusion arises regarding the dimensionality and meaning of the combined matrix (T, K) and how it integrates with the vector x, which is a 2×1 vector. The participants seek clarity on how to reconcile the differing dimensions of the matrices involved.

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  • Basic concepts of linear algebra, particularly regarding matrices and vectors
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Homework Statement



A([itex]\vec{x}[/itex]) = (F + T * x )2

F is a constant,
x is a 2×1 vector
T is a (constant) 1×2 matrixB([itex]\vec{x}[/itex]) = || K.Z.x ||2 k:3[itex]\times[/itex]3 matrix and Z:3[itex]\times[/itex]2, x the same as aboveB(x) is also R2→RC(x) = A(x) + B(x)

Homework Equations



1- I am confused how can (A + B) be represented as a (vector) norm like this:

C(x) = || (F , 0) + (T , K).Z.x ||2

, i.e., what would be the dimensionality and meaning of the matrix (T , K) ? (discrepancy between the first 1 [itex]\times[/itex] 2 entry and second 3 [itex]\times[/itex] 3?)

The Attempt at a Solution

 
Last edited:
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No solution?:frown:
 

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