Orthogonal Functions
In mathematics, two functions and are called orthogonal if their inner product is zero for f ≠ g. How the inner product of two functions is defined may vary depending on context. However, a typical definition of an inner product for functions is
with appropriate integration boundaries. Here, the asterisk indicates the complex conjugate of f.
For an intuitive perspective on this inner product, suppose approximating vectors and are created whose entries are the values of the functions f and g, sampled at equally spaced points. Then this inner product between f and g can be roughly understood as the dot product between approximating vectors and, in the limit as the number of sampling points goes to infinity. Thus, roughly, two functions are orthogonal if their approximating vectors are perpendicular (under this common inner product).
Solutions of linear differential equations with boundary conditions can often be written as a weighted sum of orthogonal solution functions (a.k.a. eigenfunctions).
Examples of sets of orthogonal functions:
- Sines and cosines
- Hermite polynomials
- Legendre polynomials
- Spherical harmonics
- Walsh functions
- Zernike polynomials
- Chebyshev polynomials
Read more about Orthogonal Functions: Generalization of Vectors
Famous quotes containing the word functions:
“One of the most highly valued functions of used parents these days is to be the villains of their childrens lives, the people the child blames for any shortcomings or disappointments. But if your identity comes from your parents failings, then you remain forever a member of the child generation, stuck and unable to move on to an adulthood in which you identify yourself in terms of what you do, not what has been done to you.”
—Frank Pittman (20th century)