Are Sin(nt) and Cos(mt) Orthogonal Over the Interval (0, 2π)?

In summary, the two functions f(t) = sin nt and g(t) = cos mt are orthogonal over the interval (0,2*pi) according to trigonometric identity 2sin a cos b = sin(a+b) - sin (a-b). This result is significant in Fourier series analysis, as it allows us to decompose a function into its orthogonal parts.
  • #1
CSNabeel
12
0

Homework Statement



Show that provided that m and n are arbitrary integers, the two functions f(t) = sin nt and g(t) = cos mt are orthogonal over the interval (0,2[tex]\pi[/tex]). Explain the significance of this result in Fourier series analysis. Hint: you may find the following trigonometric identity useful 2sin a cos b = sin(a+b) - sin (a-b)


Homework Equations





The Attempt at a Solution



[tex]\int[/tex] f(t) g(t) dt
[tex]\int[/tex] sin nt cos mt dt
[tex]\int[/tex] 0.5( sin(n+m)t - sin(n-m)t)dt
0.5[ [tex]\frac{cos(n+m)t}{n+m}[/tex] - [tex]\frac{cos(n-m)t}{n-m}[/tex] ]

put (0,2[tex]\pi[/tex]) into (n,m) respectively (sorry not good with code thing).

After subistion the final answer end up being

t over 2[tex]\pi[/tex]

this is my working out so far but what should I write about it under Fourier analysis
 
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  • #2
You don't put (0,2*pi) into (n,m). You set t=2*pi and t=0 into the anti derivative and subtract the results. There's no t in the final answer. What's cos(k*2*pi) where k is an integer?
 
  • #3
so in that case does it become

[ cos 2*pi*(n+m) / n + m ] - [ cos 2*pi*(n-m) / n - m ]

?
 
  • #4
CSNabeel said:
so in that case does it become

[ cos 2*pi*(n+m) / n + m ] - [ cos 2*pi*(n-m) / n - m ]

?

It becomes that minus [ cos 0*(n+m) / n + m ] - [ cos 0*(n-m) / n - m ]. Haven't you done definite integrals before?
 
  • #5
yeah sorry I made a mistake cancelling that because cos 0 = 1 and forget that the denominator where different

so it becomes

[ cos 2*pi*(n+m) / n + m ] - [ cos 2*pi*(n-m) / n - m ] - [1 / n + m] - [ 1 / n - m]

right?
 
  • #6
I would write that as cos(2*pi*(n+m))/(n+m) - cos(2*pi*(n-m))/(n-m) - [(1/(n+m)-1/(n-m)]. Use enough parentheses and brackets so your meaning is clear. But, yes, I think you mean the right thing. Now what's cos(k*2*pi) where k is an integer?
 
  • #7
the integral of cos(k*2*pi) is -sin(k*2*pi)/(2*pi)
 
  • #8
CSNabeel said:
the integral of cos(k*2*pi) is -sin(k*2*pi)/(2*pi)

I'm not asking you what the integral is. I'm asking you what the value of cos(k*2*pi) is where k is an 'integer' - not 'integral'. If k=1, that's cos(2*pi), if k=2, that's cos(4*pi), if k=3 that's cos(6*pi) etc etc. I'm asking you this because (n+m) and (n-m) are integers.
 
  • #9
oh well in that case cos(k*2*pi) = 1
 
  • #10
CSNabeel said:
oh well in that case cos(k*2*pi) = 1

Right, so what's the value of the integral now that you know what all the terms are?
 
  • #11
I think it's [(1/(n+m)-1/(n-m)] - [(1/(n+m)-1/(n-m)] which I think cancels out?
 
  • #12
CSNabeel said:
I think it's [(1/(n+m)-1/(n-m)] - [(1/(n+m)-1/(n-m)] which I think cancels out?

Yes, it's zero. That means f(t)=sin(nt) and g(t)=cos(mt) are orthogonal over the interval [0,2*pi] since the integral of f(t)*g(t) over that interval is zero. There is a minor technical point. What happens if n=m or n=(-m)? Then your expression has a zero in the denominator. Can you see why that's not really a problem?
 
  • #13
yeah I think so, they still cancel out even though 1/0 tends to infinity
 
  • #14
CSNabeel said:
yeah I think so, they still cancel out even though 1/0 tends to infinity

That's dangerous reasoning. The point is that if e.g. n=m, then sin((n-m)*t)=sin(0*t)=0. The cos((n-m)t)/(n-m) term isn't in the antiderivative. If you are going to be formal about the proof the you might want to make those special cases.
 
  • #15
ahhh I see. Thanks you been really helpful
 

FAQ: Are Sin(nt) and Cos(mt) Orthogonal Over the Interval (0, 2π)?

What is a Fourier Series Analysis?

A Fourier Series Analysis is a mathematical technique used to represent a periodic function as a sum of simpler trigonometric functions. It is named after French mathematician Joseph Fourier, who first introduced the concept in the 19th century.

What is the purpose of a Fourier Series Analysis?

The purpose of a Fourier Series Analysis is to break down a complex periodic function into simpler components, which can then be studied and manipulated using mathematical tools. This allows for a deeper understanding of the function's properties and behavior.

How is a Fourier Series Analysis performed?

A Fourier Series Analysis involves decomposing a periodic function into a sum of sine and cosine waves, with different amplitudes and frequencies. This is typically done using the Fourier series formula, which involves integrating the function over a period and applying orthogonality conditions.

What are some applications of Fourier Series Analysis?

Fourier Series Analysis has a wide range of applications in various fields of science and engineering. It is commonly used in signal processing, image and sound compression, heat transfer, and vibration analysis. It is also used in solving differential equations and in quantum mechanics.

Are there any limitations to Fourier Series Analysis?

While Fourier Series Analysis is a powerful tool, it does have some limitations. It can only be applied to periodic functions, and the function must be smooth and well-behaved. In addition, the convergence of the Fourier series may be slow for certain functions, requiring a large number of terms to accurately represent the function.

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