Functional equation explained

Functional equation should not be confused with Functional model.

In mathematics, a functional equation[1] [2] is, in the broadest meaning, an equation in which one or several functions appear as unknowns. So, differential equations and integral equations are functional equations. However, a more restricted meaning is often used, where a functional equation is an equation that relates several values of the same function. For example, the logarithm functions are essentially characterized by the logarithmic functional equation

log(xy)=log(x)+log(y).

If the domain of the unknown function is supposed to be the natural numbers, the function is generally viewed as a sequence, and, in this case, a functional equation (in the narrower meaning) is called a recurrence relation. Thus the term functional equation is used mainly for real functions and complex functions. Moreover a smoothness condition is often assumed for the solutions, since without such a condition, most functional equations have very irregular solutions. For example, the gamma function is a function that satisfies the functional equation

f(x+1)=xf(x)

and the initial value

f(1)=1.

There are many functions that satisfy these conditions, but the gamma function is the unique one that is meromorphic in the whole complex plane, and logarithmically convex for real and positive (Bohr–Mollerup theorem).

Examples

Fn=Fn-1+Fn-2

, where

F0=0

and

F1=1

f(x+P)=f(x)

, which characterizes the periodic functions

f(x)=f(-x)

, which characterizes the even functions, and likewise

f(x)=-f(-x)

, which characterizes the odd functions

f(f(x))=g(x)

, which characterizes the functional square roots of the function g

f(x+y)=f(x)+f(y)

(Cauchy's functional equation), satisfied by linear maps. The equation may, contingent on the axiom of choice, also have other pathological nonlinear solutions, whose existence can be proven with a Hamel basis for the real numbers

f(x+y)=f(x)f(y),

satisfied by all exponential functions. Like Cauchy's additive functional equation, this too may have pathological, discontinuous solutions

f(xy)=f(x)+f(y)

, satisfied by all logarithmic functions and, over coprime integer arguments, additive functions

f(xy)=f(x)f(y)

, satisfied by all power functions and, over coprime integer arguments, multiplicative functions

f(x+y)+f(x-y)=2[f(x)+f(y)]

(quadratic equation or parallelogram law)

f((x+y)/2)=(f(x)+f(y))/2

(Jensen's functional equation)

g(x+y)+g(x-y)=2[g(x)g(y)]

(d'Alembert's functional equation)

f(h(x))=h(x+1)

(Abel equation)

f(h(x))=cf(x)

(Schröder's equation).

f(h(x))=(f(x))c

(Böttcher's equation).

f(h(x))=h'(x)f(x)

(Julia's equation).

f(xy)=\sumgl(x)hl(y)

(Levi-Civita),

f(x+y)=f(x)g(y)+f(y)g(x)

(sine addition formula and hyperbolic sine addition formula),

g(x+y)=g(x)g(y)-f(y)f(x)

(cosine addition formula),

g(x+y)=g(x)g(y)+f(y)f(x)

(hyperbolic cosine addition formula).

f(s) = 2^s\pi^\sin\left(\frac\right)\Gamma(1-s)f(1-s) is satisfied by the Riemann zeta function, as proved here. The capital denotes the gamma function.

f(x)={f(x+1)\overx}

f(y)f\left(y+1\right)=
2
\sqrt{\pi
}f(2y)

f(z)f(1-z)={\pi\over\sin(\piz)}

(Euler's reflection formula)

ad-bc=1

, i.e.

\begin{vmatrix}a&b\c&d\end{vmatrix}

= 1, defines to be a modular form of order .

One feature that all of the examples listed above have in common is that, in each case, two or more known functions (sometimes multiplication by a constant, sometimes addition of two variables, sometimes the identity function) are inside the argument of the unknown functions to be solved for.

When it comes to asking for all solutions, it may be the case that conditions from mathematical analysis should be applied; for example, in the case of the Cauchy equation mentioned above, the solutions that are continuous functions are the 'reasonable' ones, while other solutions that are not likely to have practical application can be constructed (by using a Hamel basis for the real numbers as vector space over the rational numbers). The Bohr–Mollerup theorem is another well-known example.

Involutions

The involutions are characterized by the functional equation

f(f(x))=x

. These appear in Babbage's functional equation (1820),[3]

f(f(x))=1-(1-x)=x.

Other involutions, and solutions of the equation, include

f(x)=a-x,

f(x)=

a
x

,

and

f(x)=

b-x
1+cx

~,

which includes the previous three as special cases or limits.

Solution

One method of solving elementary functional equations is substitution.

Some solutions to functional equations have exploited surjectivity, injectivity, oddness, and evenness.

Some functional equations have been solved with the use of ansatzes, mathematical induction.

Some classes of functional equations can be solved by computer-assisted techniques.[4]

In dynamic programming a variety of successive approximation methods[5] [6] are used to solve Bellman's functional equation, including methods based on fixed point iterations.

See also

Notes

  1. Book: Rassias, Themistocles M. . Functional Equations and Inequalities . 2000 . . 3300 AA Dordrecht, The Netherlands . 0-7923-6484-8 . 335 .
  2. Book: Czerwik, Stephan . Functional Equations and Inequalities in Several Variables . 2002 . . P O Box 128, Farrer Road, Singapore 912805 . 981-02-4837-7 . 410 . limited .
  3. 10.2307/2007270. 2007270. On Certain Real Solutions of Babbage's Functional Equation. The Annals of Mathematics. 17. 3. 113–122. 1916. Ritt . J. F. . Joseph Ritt.
  4. Házy. Attila. 2004-03-01. Solving linear two variable functional equations with computer. Aequationes Mathematicae. en. 67. 1. 47–62. 10.1007/s00010-003-2703-9. 118563768. 1420-8903.
  5. Bellman, R. (1957). Dynamic Programming, Princeton University Press.
  6. Sniedovich, M. (2010). Dynamic Programming: Foundations and Principles, Taylor & Francis.

References

External links