Matrix as a Linear Map

Arindama Singh ()
Additional contact information
Arindama Singh: Indian Institute of Technology Madras, Department of Mathematics

Chapter Chapter 3 in Introduction to Matrix Theory, 2021, pp 53-80 from Springer

Abstract: Abstract Matrices can be seen as linear transformations on suitable subspaces of the n dimensional vector space. A thorough study of this notion starts with span, basis, and dimension of a subspace. Linear transformations lead to the concept of coordinate vectors and coordinate matrices. These ideas lead to change of basis matrix, equivalence, similarity and the rank factorization of a matrix.

Date: 2021
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-80481-7_3

Ordering information: This item can be ordered from
http://www.springer.com/9783030804817

DOI: 10.1007/978-3-030-80481-7_3

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().