Discrete Calculus: Derivatives & Integrals

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    Calculus Discrete
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SUMMARY

Discrete calculus exists and encompasses concepts such as finite differences and summation operators. The integral of a function over a discrete set is computed as a sum, represented mathematically as ∫_A f dμ = ∑_{a ∈ A} f(a) μ(a). The discrete derivative, known as a difference, is defined as Δ_hf(x) = f(x + h) - f(x). Techniques for solving difference equations, such as those defining the Fibonacci sequence, mirror those used in differential equations, highlighting the structural similarities between the two fields.

PREREQUISITES
  • Understanding of finite differences
  • Familiarity with difference equations
  • Basic knowledge of integrals and derivatives
  • Concept of skew derivation
NEXT STEPS
  • Research "finite differences" for deeper insights into discrete calculus
  • Study the properties and applications of difference equations
  • Explore the concept of skew derivation in mathematical analysis
  • Examine the antidifference operator and its relation to summation techniques
USEFUL FOR

Mathematicians, educators, and students interested in advanced calculus concepts, particularly those focusing on discrete mathematics and its applications in solving equations.

Eppur si muove
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Is there such thing as discrete calculus? Or are there general rules to find derivatives and integrals of functions whose domains are restricted to integers or some other discrete values?
 
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An integral over a discrete set is simply a sum! In the general case, the integral of a function [itex]f[/itex] with respect to a measure [itex]\mu[/itex] can be computed by:

[tex] \int_A f d\mu = \sum_{a \in A} f(a) \mu(a)[/tex]





There is a discrete analog of a derivative called a difference:

[tex] \Delta_hf(x) = f(x + h) - f(x)[/tex]

(when h is omitted, assume it's 1)

And difference equations have many similarities with differential equations. For example, one can "solve" for the Fibonacci sequence which is defined by a linear second-order homogenous difference equation:

[tex] \Delta^2 F + \Delta F - F = 0 | F(0) = 0, F(1) = 1[/tex]

whose solution technique is directly analogous to that of similar differential equations: (use [itex]F(r) = a^r[/itex] as a putative solution, get two linearly independent solutions, and take a linear combination that satisfies the initial conditions)

There's a more general concept here called a skew derivation (or [itex]\sigma[/itex]-derivation) of which both the ordinary derivative and this finite difference are examples.


And, of course, there's the antidifference operator, also called the summation operator, which bears a similar to indefinite integrals. For instance, you can even do summation by parts. :smile:
 
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It's more often called "finite differences" rather than "discrete calculus".

Try a google search on "finite differences". Boole wrote a book on it that is still published by Dover.
 

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