Introduction to Matrix Transformations
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Matrix Equations
A matrix equation can be written as:
Ax=bWhere:
- A is the coefficient matrix;
- x is the vector of variables;
- b is the vector of constants.
Matrix Representation of Linear Systems
Consider the linear system:
2x+y=5xβy=1This can be rewritten as:
[21β1β1β][xyβ]=[51β]Matrix Multiplication Breakdown
The multiplication of a matrix with a vector represents a linear combination:
[acβbdβ][xyβ]=[ax+bycx+dyβ]=x[acβ]+y[bdβ]Example System in Matrix Form
The system:
3x+2y=74xβy=5Can be expressed as:
[34β2β1β][xyβ]=[75β]Matrices as Transformations
A matrix transforms vectors in space.
For example:
A=[acβbdβ],Β Β v1ββ=[11β],Β Β v2ββ=[121ββ]This matrix defines how the axes transform under multiplication.
Scaling with Matrices
To apply scaling to a vector use:
S=[sxβ0β0syββ]Where:
- sxβ - the scale factor in the x-direction;
- syβ - the scale factor in the y-direction.
Example: scaling point (2, 3) by 2:
S=[20β02β],v=[23β]Then:
Sv=[46β]Rotation with Matrices
To rotate a vector by angle ΞΈ around the origin:
R=[cosΞΈsinΞΈββsinΞΈcosΞΈβ]Example: rotate (2, 3) by 90Β°:
R=[cos90ΒΊsin90ΒΊββsin90ΒΊcos90ΒΊβ]=[01ββ10β],v=[23β]Then:
Rv=[β32β]Reflection over the x-axis
Reflection matrix:
M=[10β0β1β],Using v=(2,3):
Mv=[2β3β]Shearing Transformation (x-direction shear)
Shearing shifts one axis based on the other.
To shear in the x-direction:
M=[10βk1β]If k=1.5 and v=(2,3):
Mv=[6.53β]Identity Transformation
The identity matrix performs no transformation:
I=[10β01β]For any vector v:
Iv=vThanks for your feedback!
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