ASN2 - Something Interesting: Exponential: Difference between revisions

From Class Wiki
Jump to navigation Jump to search
No edit summary
No edit summary
 
(19 intermediate revisions by the same user not shown)
Line 2: Line 2:




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


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


Where the Fourier series is <math> x1(t)= \sum_{n=0}^\infty a_n cos(\frac{ 2 \pi nt}{T}) \!</math>
Using an exponential to represent basis functions
<math> x(t)= \sum_{n=0}^\infty a_n e^{\frac{ j2 \pi nt}{T}} \!</math>


However, a more convient way is using an exponential funtion <math> e^{\frac{ j2 \pi nt}{T}} \!</math>.
To obtain the coefffients <math> a_n \!</math> the solutions are almost identical. The benefit of using the eponetial funtion is that mathematical it is simplier for solving than using the cosine function.

<math> x2(t)= \sum_{n=0}^\infty a_n e^{\frac{ j2 \pi nt}{T}} \!</math>

To solve a Fourier series equation for the coefffients <math> a_n \!</math> using the above expressions result in similar solutions but using the eponetial basis function is simplier to solving. To find the coefficients perform the dot product ' '''.''' ' as follows.

Using exponential basis function

<math> x2(t) \!</math> '''.''' <math> e^{\frac{ -j2 \pi mt}{T}} = \int_{-\frac{T}{2}}^{\frac{T}{2}}\sum_{n=0}^\infty a_n e^{\frac{ j2 \pi nt}{T}}e^{\frac{ -j2 \pi mt}{T}} dt =\sum_{n=0}^\infty a_n \int_{-\frac{T}{2}}^{\frac{T}{2}} e^{\frac{ j2 \pi (n-m)t}{T}} dt =\sum_{n=0}^\infty a_n \delta_{mn} \!</math>

Then the result is

<math>a_m=\int_{-\frac{T}{2}}^{\frac{T}{2}}x2(t)e^{\frac{ -j2 \pi mt}{T}} dt </math>

Using cosine basis function

<math> x1(t) \!</math> '''.''' <math> cos({\frac{ 2 \pi mt}{T}}) = \int_{-\frac{T}{2}}^{\frac{T}{2}}\sum_{n=0}^\infty a_n cos({\frac{ 2 \pi nt}{T}})cos{\frac{ 2 \pi mt}{T}} dt \!</math> At this point you should use a trig identity

applying this trig identity gives

<math> \frac{1}{2} \sum_{n=0}^\infty a_n \int_{-\frac{T}{2}}^{\frac{T}{2}} cos({\frac{ j2 \pi (n-m)t}{T}})cos({\frac{ j2 \pi (n+m)t}{T}}) dt =\frac{1}{2}\sum_{n=0}^\infty a_n T \delta_{mn} \!</math>

Then the result is

<math>a_m=\int_{-\frac{T}{2}}^{\frac{T}{2}}x1(t)cos({\frac{ 2 \pi mt}{T}}) dt </math>

Latest revision as of 22:52, 13 December 2009

Back to my Home Page


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

One way of representing a basis function is with cosine .

Where the Fourier series is

However, a more convient way is using an exponential funtion .

To solve a Fourier series equation for the coefffients using the above expressions result in similar solutions but using the eponetial basis function is simplier to solving. To find the coefficients perform the dot product ' . ' as follows.

Using exponential basis function

.

Then the result is

Using cosine basis function

. At this point you should use a trig identity

applying this trig identity gives

Then the result is