**NOTE: THIS DOCUMENT IS OBSOLETE, PLEASE CHECK THE NEW
VERSION:** "Mathematics of the Discrete
Fourier Transform (DFT), with Audio Applications --- Second
Edition", by Julius
O. Smith III, W3K
Publishing, 2007, ISBN 978-0-9745607-4-8. - Copyright ©
*2017-09-28* by Julius O. Smith III -
Center for Computer Research
in Music and Acoustics (CCRMA), Stanford University

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Informal Derivation ofTaylor Series ExpansionWe have a function and we want to approximate it using anth-order

polynomial:

where , which is obviously the approximation error, is called the “remainder term.” We may assume and arereal, but the following derivation generalizes unchanged to the complex case.Our problem is to find fixed constants so as to obtain the best approximation possible. Let’s proceed optimistically as though the approximation will be perfect, and assume for all (), given the right values of . Then at we must have

That’s one constant down and to go! Now let’s look at the first derivative of with respect to , again assuming that :

Evaluating this at gives

In the same way, we find

where denotes the th derivative of with respect to, evaluated at . Solving the above relations for the desired constants yields

Thus, defining (as it always is), we have derived the following polynomial approximation:

This is the th-order Taylor series expansion of about the point. Its derivation was quite simple. The hard part is showing that the approximation error (remainder term ) is small over a wide interval of values. Another “math job” is to determine the conditions under which the approximation error approaches zero for all as the order goes to infinity. The main point to note here is that the form of the Taylor series expansion itself is simple to derive.