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Mathematics LibreTexts

3: Linear Transformations and Matrix Algebra

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Note 3.1

Learn about linear transformations and their relationship to matrices.

In practice, one is often lead to ask questions about the geometry of a transformation: a function that takes an input and produces an output. This kind of question can be answered by linear algebra if the transformation can be expressed by a matrix.

  • 3.0: Prelude to Linear Transformations and Matrix Algebra
    This page explores the non-linear complexities of a robot arm's joint movements and hand positions through the transformation function f(θ,ϕ,ψ). It discusses the relationship between matrices and transformations, covering how transformations can be expressed with matrices, their properties, and how matrix multiplication relates to composition. The chapter culminates in understanding matrix arithmetic and solving matrix equations.
  • 3.1: Matrix Transformations
    This page provides an overview of matrix transformations in linear algebra, emphasizing their geometric interpretation in R2 and their applications in robotics and computer graphics. It discusses key concepts such as domain, codomain, range, and the identity transformation while illustrating various transformations like rotation, shear, and projection.
  • 3.2: One-to-one and Onto Transformations
    This page discusses the concepts of one-to-one and onto transformations in linear algebra, focusing on matrix transformations. It defines one-to-one as each output having at most one input and outlines examples and theorems related to this property. The text emphasizes that a transformation is onto if every output corresponds to some input.
  • 3.3: Linear Transformations
    This page covers linear transformations and their connections to matrix transformations, defining properties necessary for linearity and providing examples of both linear and non-linear transformations. It highlights the importance of the zero vector, standard coordinate vectors, and defines transformations like rotations, dilations, and the identity transformation.
  • 3.4: Matrix Multiplication
    This page explores the interplay between compositions of transformations and matrix multiplication in linear algebra. It defines the composition of transformations, illustrates their properties, including non-commutativity and associativity, and connects these concepts to matrix operations. The Row-Column Rule for matrix multiplication is explained, alongside the implications of this non-commutative nature.
  • 3.5: Matrix Inverses
    This page covers invertible matrices and transformations in linear algebra, defining conditions for 2x2 matrices to be invertible based on determinants. It details methods for computing inverses, including row reduction for n×n matrices. The text emphasizes the role of matrix inverses in solving linear systems and describes invertible transformations in Rn, highlighting examples of one-to-one functions.
  • 3.6: The Invertible Matrix Theorem
    This page explores the Invertible Matrix Theorem, detailing equivalent conditions for a square matrix A to be invertible, such as having n pivots and unique solutions for Ax=b. It includes proofs and examples, emphasizes the theorem's importance, and presents a corollary linking inverses to invertibility.


This page titled 3: Linear Transformations and Matrix Algebra is shared under a GNU Free Documentation License 1.3 license and was authored, remixed, and/or curated by Dan Margalit & Joseph Rabinoff via source content that was edited to the style and standards of the LibreTexts platform.

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