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Frobenius Norm 📂Matrix Algebra

Frobenius Norm

Definition 1

The norm of a matrix A=(aij)Cm×nA = \left( a_{ij} \right) \in \mathbb{C}^{m \times n} is defined as follows and is called the Frobenius norm. AF=ijaij2=Tr(AA) \left\| A \right\|_{F} = \sqrt{ \sum_{ij} \left| a_{ij} \right|^{2} } = \sqrt{ \text{Tr} \left( A A^{\ast} \right) }

Explanation

The Frobenius norm is also known as the Hilbert-Schmidt norm. n=1n = 1, i.e., in the space of mm-dimensional vectors, it becomes the Euclidean norm, therefore it can be seen as a natural generalization of the Euclidean norm.

The name Frobenius may seem grand, but the definition itself is not difficult, so it’s easy to understand.


  1. 김상동. (2012). 수치행렬해석: p44. ↩︎