Taylor series in terms of discrete derivative

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SUMMARY

The discussion focuses on the application of Taylor series in the context of discrete derivatives, specifically utilizing the Hilger derivative in time scale calculus. The Taylor theorem is expressed as f(t) = \sum_{k=0}^{n-1}f^{\Delta^k}(a)\, h_{k}(t, a) \, + R, where h_k(t,s) is defined recursively. The key distinction is that in discrete calculus, the term h_k(t,s) = \frac{(t-s)(t-s-1)\ldots(t-s-k+1)}{k!} serves a similar purpose to the continuous case's h_k(t,s) = \frac{(t-s)^k}{k!}. This highlights the unification of continuous and discrete calculus through time scale calculus.

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  • Understanding of Taylor series and its formulation
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Jhenrique
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All analitic function can be express how: f(x) = \frac{1}{0!} \frac{d^0f}{dx^0}(x_0) (x - x_0)^0 + \frac{1}{1!} \frac{d^1 f}{dx^1}(x_0) (x - x_0)^1 + \frac{1}{2!} \frac{d^2f}{dx^2}(x_0) (x - x_0)^2 + \frac{1}{3!} \frac{d^3f}{dx^3}(x_0) (x - x_0)^3 + ... that is the taylor series of the function f(x).

Analogously, should exist a taylor series that use the discrete derivative ##\frac{\Delta f}{\Delta x} = f[x+1] - f[x]##. I found this
NumberedEquation4.gif
in wolframpage http://mathworld.wolfram.com/ForwardDifference.html but appears strange. I didn't undertood what such series means. Someone can explain me?
 
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I'm going to use notation from time scale calculus, which is a unification of continuous and discrete calculus. It makes my message more obvious.

A time scale is a non-empty closed subset ##\mathbb{T}\subset\mathbb{R}##.
Given a function ##f : \mathbb{T}\to\mathbb{R}##, we define the (Hilger) derivative ##f^{\Delta}## in such a way such that
  • if ##\mathbb{T} = \mathbb{R}## then Hilger derivative is equal to ##f^{\Delta}(t) = f'(t)## and
  • if ##\mathbb{T} = \mathbb{Z}## then Hilger derivative is equal to ##f^{\Delta}(t) = \Delta f(t)##.

To study the Taylor theorem, we also have "h-polynomials" which are defined
##h_{0}(t,s) = 1## and
##h_{k+1}(t,s) = \int_s^t h_k(\tau, s) \, \Delta \tau##.
In words "start with the constant and keep integrating over and over".
  • if ##\mathbb{T} = \mathbb{R}## then ##h_k(t,s) = \frac{(t-s)^k}{k!}## and
  • if ##\mathbb{T} = \mathbb{Z}## then ##h_k(t,s) = \frac{(t-s)(t-s-1)(t-s-2)\ldots(t-s-k+1)}{k!}##

The Taylor theorem itself is
##f(t) = \sum_{k=0}^{n-1}f^{\Delta^k}(a)\, h_{k}(t, a) \, + R##
where R is the remainder (I'm not going to write down the remainder term).
  • if ##\mathbb{T} = \mathbb{R}## then
    ##f(t) = f(a) + f'(a) \frac{t-s}{1!} + f''(a) \frac{(t-s)^2}{2!}+\ldots+f^{(k)}(a) \frac{(t-s)^k}{k!} + \ldots## and
  • if ##\mathbb{T} = \mathbb{Z}## then
    ##f(t) = f(a) + \Delta f(a) \frac{t-s}{1!} + \Delta^2 f(a) \frac{(t-s)(t-s-1)}{2!}+\ldots+\Delta^{k}f(a) \frac{(t-s)(t-s-1)\ldots(t-s-k+1)}{k!} + \ldots##.


The important thing is that in discrete calculus these ##\frac{(t-s)(t-s-1)(t-s-2)\ldots(t-s-k+1)}{k!}## serve the same role as ##\frac{(t-s)^k}{k!}## does in the continuous calculus.
 
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good answer!
 

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