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Norms, Adjoints, and Singular Value Decomposition

In: Multidimensional Analysis

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  • George W. Hart

    (Columbia University, Department of Electrical Engineering)

Abstract

Norms for measuring vectors and matrices, adjoints, and the singular value decomposition (SVD) are all areas where traditional methods are basis-dependent and/or dimensionally inhomogeneous. The methods presented in this chapter correct these problems.

Suggested Citation

  • George W. Hart, 1995. "Norms, Adjoints, and Singular Value Decomposition," Springer Books, in: Multidimensional Analysis, chapter 4, pages 119-144, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4612-4208-6_5
    DOI: 10.1007/978-1-4612-4208-6_5
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