How is this summation approx valid?

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In summary, the average of n times a sine function with frequency f_o and phase 2phi is approximately 0, unless f_o is close to 0 or 1/2. If f_o and phi are randomly chosen, the average will be small, potentially O(N^(-1/2)) or o(1).
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sauravrt
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I came across this approximation in a book. I am not sure why this approximation is valid..

[tex]\frac{1}{N}\sum_{n=0}^{N-1}n.sin[4\pi f_o n + 2\phi] \approx 0[/tex]

[tex]f_o[/tex] is not near 0 or 1/2

Saurav
 
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  • #2
Perhaps it's because you are averaging over a sin function, which has average 0?
 
  • #3
Pretty much. Unless something funny is going on, the positives and the negatives should pretty well cancel out.

If it is -- if you manage to get sin = 1 at each point -- you can get as high as (N - 1)/2. But for randomly-chosen f_0 and phi, I'd expect to get something pretty small. Maybe not O(N^(-1/2)), but certainly o(1).
 

FAQ: How is this summation approx valid?

How does summation approximation work?

Summation approximation is a mathematical method used to estimate the value of a summation by using a simplified version of the original equation. This is done by breaking the summation into smaller, more manageable parts and then summing them together to get an approximate value.

Is summation approximation accurate?

Summation approximation can provide a fairly accurate estimate of the value of a summation, but it is not always exact. The accuracy of the approximation depends on the number of terms used and the complexity of the original equation.

When should summation approximation be used?

Summation approximation is commonly used when the original equation is too complex or time-consuming to calculate directly. It can also be used when the exact value of the summation is not necessary, and an estimate is sufficient for the given application.

How do you choose the number of terms to use in summation approximation?

The number of terms used in summation approximation can vary depending on the accuracy required for the given application. Generally, using more terms will result in a more accurate estimate, but it will also require more time and resources. A balance should be struck between accuracy and practicality.

Are there any limitations to summation approximation?

Yes, summation approximation has limitations. It may not work for all types of summations, particularly those involving irrational or infinite values. Additionally, the accuracy of the approximation may decrease as the number of terms in the summation increases. It is important to carefully consider the limitations before using summation approximation in any application.

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