23.07.2012 Views

Linear Algebra

Linear Algebra

Linear Algebra

SHOW MORE
SHOW LESS

Create successful ePaper yourself

Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.

Section III. Basis and Dimension 133<br />

also write R3 = xy-plane + yz-plane. To check this, we simply note that any<br />

�w ∈ R3 can be written<br />

⎛<br />

⎝ w1<br />

⎞ ⎛<br />

w2⎠<br />

=1· ⎝ w1<br />

⎞ ⎛<br />

w2⎠<br />

+1· ⎝<br />

0<br />

0<br />

⎞<br />

0 ⎠<br />

w3<br />

as a linear combination of a member of the xy-plane and a member of the<br />

yz-plane.<br />

The above definition gives one way in which a space can be thought of as a<br />

combination of some of its parts. However, the prior example shows that there is<br />

at least one interesting property of our benchmark model that is not captured by<br />

the definition of the sum of subspaces. In the familiar decomposition of R3 ,we<br />

often speak of a vector’s ‘x part’or‘y part’or‘z part’. That is, in this model,<br />

each vector has a unique decomposition into parts that come from the parts<br />

making up the whole space. But in the decomposition used in Example 4.4, we<br />

cannot refer to the “xy part” of a vector — these three sums<br />

⎛ ⎞ ⎛ ⎞ ⎛ ⎞ ⎛ ⎞ ⎛ ⎞ ⎛ ⎞ ⎛ ⎞<br />

1 1 0 1 0 1 0<br />

⎝2⎠<br />

= ⎝2⎠<br />

+ ⎝0⎠<br />

= ⎝0⎠<br />

+ ⎝2⎠<br />

= ⎝1⎠<br />

+ ⎝1⎠<br />

3 0 3 0 3 0 3<br />

all describe the vector as comprised of something from the first plane plus something<br />

from the second plane, but the “xy part” is different in each.<br />

That is, when we consider how R 3 is put together from the three axes “in<br />

some way”, we might mean “in such a way that every vector has at least one<br />

decomposition”, and that leads to the definition above. But if we take it to<br />

mean “in such a way that every vector has one and only one decomposition”<br />

then we need another condition on combinations. To see what this condition<br />

is, recall that vectors are uniquely represented in terms of a basis. We can use<br />

this to break a space into a sum of subspaces such that any vector in the space<br />

breaks uniquely into a sum of members of those subspaces.<br />

4.5 Example The benchmark is R 3 with its standard basis E3 = 〈�e1,�e2,�e3〉.<br />

The subspace with the basis B1 = 〈�e1〉 is the x-axis. The subspace with the<br />

basis B2 = 〈�e2〉 is the y-axis. The subspace with the basis B3 = 〈�e3〉 is the<br />

z-axis. The fact that any member of R 3 is expressible as a sum of vectors from<br />

these subspaces<br />

w3<br />

⎛<br />

⎝ x<br />

⎞ ⎛<br />

y⎠<br />

= ⎝<br />

z<br />

x<br />

⎞ ⎛<br />

0⎠<br />

+ ⎝<br />

0<br />

0<br />

⎞ ⎛<br />

y⎠<br />

+ ⎝<br />

0<br />

0<br />

⎞<br />

0⎠<br />

z<br />

is a reflection of the fact that E3 spans the space — this equation<br />

⎛<br />

⎝ x<br />

⎞ ⎛<br />

y⎠<br />

= c1 ⎝<br />

z<br />

1<br />

⎞ ⎛<br />

0⎠<br />

+ c2 ⎝<br />

0<br />

0<br />

⎞ ⎛<br />

1⎠<br />

+ c3 ⎝<br />

0<br />

0<br />

⎞<br />

0⎠<br />

1

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!