Linear Algebra: UNIT I: Vector Spaces

Definition of Linear Dependence and Linear Independence

Vector Spaces: Definition of Linear Dependence and Linear Independence

LINEAR DEPENDENCE AND LINEAR INDEPENDENCE

 

Definition: Linear Dependences

A subset S of a vector space V is called linearly dependent if there exist a finite number of distinct vectors u1, u2, u3…. un in S and scalars a1, a2, a3 ... an not all zero, such that

    а1u1 + а2u2 + а3u3 +.. .. + аnun = 0.

In this case we say that the vectors of S are linearly dependent.

For any vectors u1, u2, u3... un we have а1u1 + а2u2 + а3u3 +.. .. + аnun = 0. If а1= а2= а3 =…. аn=0. We call this the trivial representation of 0 as a linear combination of u1, u2, u3 ... un. Thus for a set to be linearly dependent, there must exist a non−trivial representation of 0 as a linear combination of vectors in the set.

Consequently, any subset of a vector space that contains the zero vector is linearly dependent, because 0= 1.0 is a nontrivial representation of 0 as a linear combination of vectors in the set.


Definition: Linear Independence

A subset S of a vector space that is not linear dependent is called linearly independent. We also say that the vectors of S are linearly independent.

The following facts about linearly independent sets are true in any vector space.

 (i) The empty set is linearly independent, for linearly dependent, sets must be non−empty.

(ii) A set consisting of a single non−zero vector is linearly independent. If {u} is linearly dependent, then au= 0 for some non−zero scalar a.

  u = a‒1(au) = a‒1 0 = 0.

(iii) A set is linearly independent if and only if the only representations of 0 as linear combinations of its vectors are trivial representations.

 

Linear Algebra: UNIT I: Vector Spaces : Tag: maths, mathematics : - Definition of Linear Dependence and Linear Independence


Linear Algebra: UNIT I: Vector Spaces



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