Matrix transform vs linear transform

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Every matrix transformation from R-n to R-m qualifies as a linear transformation, but not all linear transformations can be represented as matrix transformations. David Lay's text emphasizes that matrix transformations are specific implementations of mappings, while linear transformations pertain to the properties of those mappings. The discussion seeks counterexamples of linear transformations that do not correspond to matrix transformations, highlighting a gap in available literature. Additionally, the conversation touches on the use of homogeneous coordinates in 3D graphics, where transformation matrices can represent both affine and perspective projections, despite being labeled as "homogeneous." Understanding these distinctions is crucial for applications in linear algebra and computer graphics.
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Every matrix transformation from R-n to R-m is a linear transformation. The converse of this is not true: every linear transformation is not a matrix transformation.

According to David Lay's text, Linear Algebra, the term matrix transformation describes how a mapping is implemented, while the term linear transformation focus on a property of the mapping. His text is replete with examples of matrix transforms which are linear tranforms, but silent on examples of linear transforms that are not matrix transforms.

Where can I find a counterexample that illustrates a linear transformation which is not a matrix tranformation?

Also, as I contemplate future posts, is there a link that explains how to format my questions, equations, etc in LyX or something similar? Thanks.
 
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If Wikipedia is to be believed, here is something you can use:
[PLAIN]http://en.wikipedia.org/wiki/Transformation_matrix said:
Linear[/PLAIN] transformations are not the only ones that can be represented by matrices. Using homogeneous coordinates, both affine transformations and perspective projections on Rn can be represented as linear transformations on RPn+1 (that is, n+1-dimensional real projective space). For this reason, 4x4 transformation matrices are widely used in 3D computer graphics.

3-by-3 or 4-by-4 transformation matrices containing homogeneous coordinates are often called, somewhat improperly, "homogeneous transformation matrices". However, the transformations they represent are, in most cases, definitely non-homogeneous and non-linear (like translation, roto-translation or perspective projection). And even the matrices themselves look rather heterogeneous, i.e. composed of different kinds of elements (see below). Since they are multi-purpose transformation matrices, capable of representing both affine and projective transformations, they might be called "general transformation matrices", or, depending on the application, "affine transformation" or "perspective projection" matrices. Moreover, since the homogeneous coordinates describe a projective vector space, they can also be called "projective space transformation matrices".
Hope that helps.
 
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Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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