ASN2 - Something Interesting: Exponential: Difference between revisions

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Fourier Series  
Here's an demonstration of using the expontential function in an Fourier Series example.


Using cosine to represent the basis functions
One way of representing a basis function is with cosine.
<math> x1(t)= \sum_{n=0}^\infty a_n cos(\frac{ 2 \pi nt}{T}) \!</math>
<math> x1(t)= \sum_{n=0}^\infty a_n cos(\frac{ 2 \pi nt}{T}) \!</math>


Using an exponential to represent basis functions
However, a more convient way is using an exponential funtion.
<math> x1(t)= \sum_{n=0}^\infty a_n e^{\frac{ j2 \pi nt}{T}} \!</math>
<math> x1(t)= \sum_{n=0}^\infty a_n e^{\frac{ j2 \pi nt}{T}} \!</math>



Revision as of 20:54, 13 December 2009

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Here's an demonstration of using the expontential function in an Fourier Series example.

One way of representing a basis function is with cosine. x1(t)=n=0ancos(2πntT)

However, a more convient way is using an exponential funtion. x1(t)=n=0anej2πntT

To solve for the coefffients an the solutions for both are almost identical. The benefit of using the eponetialinstead of cosine is that mathematical it is simplier for solving.

To solve for the coefficients do the dot product ' . ' of the basis function and x(t)


x2(t) . ej2πmtT=T2T2n=0anej2πntTej2πmtTdt=n=0anT2T2ej2π(nm)tTdt=n=0anTδmn

Then am=T2T2x2(t)ej2πmtTdt


x1(t) . cos(2πmtT)=T2T2n=0ancos(2πntT)cos2πmtTdt At this point you should use a trig identity

applying this trig identity gives

12n=0anT2T2cos(j2π(nm)tT)cos(j2π(n+m)tT)dt=12n=0anTδmn

Then am=T2T2x1(t)cos(2πmtT)dt