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| Linear algebra is fundamentally algebra that can be applied to any linear space. | Linear algebra is algebra that can be applied to any linear space to study [[LinearAlgebra/LinearMapping|linear mappings]]. It is helpful to then define '''linearity'''. |
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| 2. Commutatibility of addition | 2. Commutability of addition |
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| 5. Commutatibility of scalar multiplication | 5. Commutability of scalar multiplication |
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| Functions also obey these axioms. | Functions and [[Calculus/Derivative|derivatives]] are also [[LinearAlgebra/LinearMapping|transformations]], often in polynomial vector space (''P,,n,,''). For example, the transformation ''T'' representing differentiation with respect to ''x'' in the domain ''P,,3,,'' is formalized as ''T: P,,3,, -> P,,2,,''. |
Linearity
Linear algebra is algebra that can be applied to any linear space to study linear mappings. It is helpful to then define linearity.
Axioms
A linear space obeys these axioms.
- Associativity of addition
(a + b) + c = a + (b + c)
- Commutability of addition
a + b = b + a
There is some 0 space that has an additive identity property
0 + a = a
There is some -a space for every a space that has an additive identity property
a + (-a) = 0
- Commutability of scalar multiplication
if a and b are scalars while c is a space
a(bc) = (ab)c
- Identity of scalar multiplication
1a = a
- Distributivity of scalar multiplication
if a is a scalar while b and c are spaces
a(b + c) = ab + ac
- Distributivity of space multiplication
if a and b are scalars while c is a space
(a + b)c = ac + bc
Vectors, matrices, and subspaces all obey these axioms, laying the foundation for linear algebra.
Functions and derivatives are also transformations, often in polynomial vector space (Pn). For example, the transformation T representing differentiation with respect to x in the domain P3 is formalized as T: P3 -> P2.
