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1.3 What are Linear Functions? 19<br />

Function = Transformation = Operator<br />

And now for a hint at the power of <strong>linear</strong> algebra.<br />

examples (A-D) can all be restated as<br />

The questions in<br />

Lv = w<br />

where v is an unknown, w a known vector, and L is a known <strong>linear</strong> transformation.<br />

To check that this is true, one needs to know the rules for adding<br />

vectors (both inputs and outputs) and then check <strong>linear</strong>ity of L. Solving the<br />

equation Lv = w often amounts to solving systems of <strong>linear</strong> equations, the<br />

skill you will learn in Chapter 2.<br />

A great example is the derivative operator.<br />

Example 4 (The derivative operator is <strong>linear</strong>)<br />

For any two functions f(x), g(x) and any number c, in calculus you probably learnt<br />

that the derivative operator satisfies<br />

1.<br />

d<br />

dx (cf) = c d<br />

dx f,<br />

d<br />

d<br />

2.<br />

dx<br />

(f + g) =<br />

dx f + d<br />

dx g.<br />

If we view functions as vectors with addition given by addition of functions and with<br />

scalar multiplication given by multiplication of functions by constants, then these<br />

familiar properties of derivatives are just the <strong>linear</strong>ity property of <strong>linear</strong> maps.<br />

Before introducing matrices, notice that for <strong>linear</strong> maps L we will often<br />

write simply Lu instead of L(u). This is because the <strong>linear</strong>ity property of a<br />

19

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