Gram-Schmidt Process
Bachelor of Science in Mathematics · University · Linear Algebra
The Gram-Schmidt process is a method for orthogonalizing a set of vectors in an inner product space. It is used to construct an orthonormal basis for a subspace, which can be useful for solving systems of linear equations, finding eigenvalues and eigenvectors, and other applications.
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Das gehört dazu
- Definition and statement of the Gram-Schmidt process
- Steps involved in applying the Gram-Schmidt process
- Properties of the Gram-Schmidt process
- Applications of the Gram-Schmidt process
- Advantages and disadvantages of the Gram-Schmidt process
Stichworte
- Gram-Schmidt Process
- Orthogonalization
- Inner Product
- Orthonormal Basis
- Linear Independence