The finite difference is the discrete analog of the derivative. The finite forward difference of a function is defined as
|
(1)
|
and the finite backward difference as
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(2)
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The forward finite difference is implemented in the Wolfram Language as DifferenceDelta[f, i].
If the values are tabulated at spacings , then the notation
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(3)
|
is used. The th
forward difference would then be written as
, and similarly, the
th backward difference
as
.
However, when
is viewed as a discretization of the continuous
function
,
then the finite difference is sometimes written
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(4)
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(5)
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where
denotes convolution and
is the odd impulse pair. The finite difference
operator can therefore be written
|
(6)
|
An th
power has a constant
th finite difference. For example, take
and make a difference table,
|
(7)
|
The
column is the constant 6.
Finite difference formulas can be very useful for extrapolating a finite amount of data in an attempt
to find the general term. Specifically, if a function is known at only a few discrete values
,
1, 2, ... and it is desired to determine the analytical form of
, the following procedure can be used if
is assumed to be a polynomial
function. Denote the
th value in the sequence of interest
by
.
Then define
as the forward difference
,
as the second forward
difference
,
etc., constructing a table as follows
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(8)
| |
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(9)
| |
|
(10)
| |
|
(11)
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Continue constructing the difference table through the last available row. The unique polynomial of degree at most interpolating the
values
,
, ...,
is then given by
|
(12)
| |||
|
(13)
|
Here ,
so
,
,
etc. This equation is called Newton's
forward difference formula. To see a particular example, consider a sequence
with first few values of 1, 19, 143, 607, 1789, 4211, 8539, .... The difference
table is then given by
|
(14)
|
Reading off the first number in each row gives ,
,
,
,
. Plugging these in gives the equation
|
(15)
| |||
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(16)
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which indeed fits the original data exactly.
Formulas for the derivatives are given by
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(17)
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(18)
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(19)
| |||
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(20)
| |||
|
(21)
| |||
|
(22)
| |||
|
(23)
| |||
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(24)
| |||
|
(25)
| |||
|
(26)
| |||
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(27)
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(Beyer 1987, pp. 449-451; Zwillinger 1995, p. 705).
Formulas for integrals of finite differences
|
(28)
|
are given by Beyer (1987, pp. 455-456).
Finite differences lead to difference equations, finite analogs of differential equations. In fact, umbral calculus displays many elegant analogs of well-known identities for continuous functions. Common finite difference schemes for partial differential equations include the Crank-Nicolson method, Du Fort-Frankel method, and Laasonen method.