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What is the orthogonality of sine and cosine function?

Posted on March 5, 2021 by Sherryl Cole

Table of Contents

  • What is the orthogonality of sine and cosine function?
  • How do you prove orthogonality?
    • What is orthogonal basis function?
    • What is orthogonality rule?
  • What is the meaning of orthogonal functions?
  • What are orthogonal basis functions?
    • How to prove orthogonality relations in exponential form?
    • Which is mutually orthogonal in n = 1 ∞?

What is the orthogonality of sine and cosine function?

So, in previous examples we’ve shown that on the interval −L≤x≤L − L ≤ x ≤ L the two sets are mutually orthogonal individually and here we’ve shown that integrating a product of a sine and a cosine gives zero. Therefore, as a combined set they are also mutually orthogonal.

How do you prove orthogonality?

In Euclidean space, two vectors are orthogonal if and only if their dot product is zero, i.e. they make an angle of 90° (π/2 radians), or one of the vectors is zero. Hence orthogonality of vectors is an extension of the concept of perpendicular vectors to spaces of any dimension.

Why sine and cosine functions are orthogonal to each other?

I have often come across the concept of orthogonality and orthogonal functions e.g in fourier series the basis functions are cos and sine, and they are orthogonal. For vectors being orthogonal means that they are actually perpendicular such that their dot product is zero.

Are sine functions orthogonal?

Just integrate with respect to x first. The various two dimensional functions, sin(mx)×sin(ny), cos(mx)×sin(ny), cos(mx)×cos(ny), sin(mx)×cos(ny), are all pairwise orthogonal.

What is orthogonal basis function?

As with a basis of vectors in a finite-dimensional space, orthogonal functions can form an infinite basis for a function space. Conceptually, the above integral is the equivalent of a vector dot-product; two vectors are mutually independent (orthogonal) if their dot-product is zero.

What is orthogonality rule?

Loosely stated, the orthogonality principle says that the error vector of the optimal estimator (in a mean square error sense) is orthogonal to any possible estimator. The orthogonality principle is most commonly stated for linear estimators, but more general formulations are possible.

Are sin and cos Orthonormal?

So, sin(x) and cos(x) are orthogonal, but they are not normalized.

What is an orthogonal set of functions?

What is the meaning of orthogonal functions?

: two mathematical functions such that with suitable limits the definite integral of their product is zero.

What are orthogonal basis functions?

How to prove the orthogonality of Sine and cosine?

If k=0 then the integrand is 1 and the integral is 2π. Then to prove the orthogonality relations just substitute the exponential forms for sine and cosine, i.e. cos (nx)= (exp (inx)+exp (-inx))/2 etc. and the result falls out.

Which is the non-zero term in the orthogonality relation?

Now the orthogonality relations tell us that almost every term in this sum will integrate to 0. In fact, the only non-zero term is the n = 2 cosine term 1 L π π a 2 cos L 2 t cos 2 t dt −L L L and the orthogonality relations for the case n = m = 2 show this integral is equal to a 2 as claimed. a Why the denominator of 2 in 0? 2

How to prove orthogonality relations in exponential form?

Then to prove the orthogonality relations just substitute the exponential forms for sine and cosine, i.e. cos(nx)=(exp(inx)+exp(-inx))/2 etc. and the result falls out.

Which is mutually orthogonal in n = 1 ∞?

( n π x L) } n = 1 ∞ are mutually orthogonal on −L ≤ x ≤ L − L ≤ x ≤ L as individual sets and as a combined set. We will also be needing the results of the integrals themselves, both on −L ≤ x ≤ L − L ≤ x ≤ L and on 0 ≤ x ≤ L 0 ≤ x ≤ L so let’s also summarize those up here as well so we can refer to them when we need to.

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