Orthogonal functions

In mathematics, orthogonal functions belong to a function space which is a vector space that has a bilinear form. When the function space has an interval as the domain, the bilinear form may be the integral of the product of functions over the interval:

The functions and are orthogonal when this integral is zero, i.e. whenever . 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.

Suppose is a sequence of orthogonal functions of nonzero L2-norms . It follows that the sequence is of functions of L2-norm one, forming an orthonormal sequence. To have a defined L2-norm, the integral must be bounded, which restricts the functions to being square-integrable.

Trigonometric functionsEdit

Several sets of orthogonal functions have become standard bases for approximating functions. For example, the sine functions sin nx and sin mx are orthogonal on the interval   when   and n and m are positive integers. For then


and the integral of the product of the two sine functions vanishes.[1] Together with cosine functions, these orthogonal functions may be assembled into a trigonometric polynomial to approximate a given function on the interval with its Fourier series.


If one begins with the monomial sequence   on the interval   and applies the Gram–Schmidt process, then one obtains the Legendre polynomials. Another collection of orthogonal polynomials are the associated Legendre polynomials.

The study of orthogonal polynomials involves weight functions   that are inserted in the bilinear form:


For Laguerre polynomials on   the weight function is  .

Both physicists and probability theorists use Hermite polynomials on  , where the weight function is   or  

Chebyshev polynomials are defined on   and use weights   or  .

Zernike polynomials are defined on the unit disk and have orthogonality of both radial and angular parts.

Binary-valued functionsEdit

Walsh functions and Haar wavelets are examples of orthogonal functions with discrete ranges.

Rational functionsEdit

Plot of the Chebyshev rational functions of order n=0,1,2,3 and 4 between x=0.01 and 100.

Legendre and Chebyshev polynomials provide orthogonal families for the interval [−1, 1] while occasionally orthogonal families are required on [0, ∞). In this case it is convenient to apply the Cayley transform first, to bring the argument into [−1, 1]. This procedure results in families of rational orthogonal functions called Legendre rational functions and Chebyshev rational functions.

In differential equationsEdit

Solutions of linear differential equations with boundary conditions can often be written as a weighted sum of orthogonal solution functions (a.k.a. eigenfunctions), leading to generalized Fourier series.

See alsoEdit


  1. ^ Antoni Zygmund (1935) Trigonometrical Series, page 6, Mathematical Seminar, University of Warsaw
  • George B. Arfken & Hans J. Weber (2005) Mathematical Methods for Physicists, 6th edition, chapter 10: Sturm-Liouville Theory — Orthogonal Functions, Academic Press.
  • Price, Justin J. (1975). "Topics in orthogonal functions". American Mathematical Monthly. 82: 594–609. doi:10.2307/2319690.
  • Giovanni Sansone (translated by Ainsley H. Diamond) (1959) Orthogonal Functions, Interscience Publishers.

External linksEdit