Representation of vectors by basis is Unique

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SUMMARY

The representation of vectors by any basis is unique, as established in the discussion. The proof involves expanding a vector \( \vec{w} \) into a basis set \( \{\hat{w}_i\} \) using two different sets of coefficients, \( a_i \) and \( b_i \). By demonstrating that \( \sum_i (a_i - b_i)\hat{w}_i = 0 \) and leveraging the independence of the vectors, it is concluded that \( a_i = b_i \) for all \( i \). This confirms the uniqueness of representation in linear algebra.

PREREQUISITES
  • Understanding of linear independence and span in vector spaces
  • Familiarity with basis sets in linear algebra
  • Knowledge of vector representation and coefficient expansion
  • Proficiency in manipulating summations and equations
NEXT STEPS
  • Study the concept of linear independence in depth
  • Learn about the properties of basis sets in vector spaces
  • Explore the implications of the uniqueness of vector representation
  • Investigate applications of basis transformations in computational contexts
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Students of linear algebra, educators teaching vector spaces, and mathematicians interested in the foundational principles of vector representation.

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Homework Statement



Prove:

Representation of vectors by any basis is unique.

Homework Equations





The Attempt at a Solution



The minimal span set and the maximum linearly independent set gives a basis.
 
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Try expanding a vector w into a basis set {w_i} using two different sets of coefficients i.e.

[itex]\vec{w}=\sum_i a_i \hat{w}_i[/itex] and [itex]\vec{w}=\sum_i b_i \hat{w}_i[/itex]

Then just show that a_i=b_i for all i.
 
Last edited:
gabbagabbahey's notation, think about the fact that
[itex]\sum_i (a_i- b_i)\hat{w}_i= 0[/itex] and use the fact that the vectors are independent.
 

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