Introduction
Calculating derivatives is one of the most important and elementary topics in calculus. The geometric meaning of the derivative is given as the slope of the function at a given point. To calculate the slope of a function , the approximate slope is first written as a ratio of , where and . Then, letting , the error in the approximate slope expression is reduced until the exact slope of the function is calculated at point x (Thomas & Finney, 1984; Strang, 1991).
First, the abovementioned basic definition of the derivative is expressed in a more general form. and are expressed as functional forms of the limiting parameter. The properties of the generalized form are discussed. The error introduced without taking the limit is calculated for the classical and generalized definitions. A special case of the generalized definition that covers scaling and translational transformations is also given. Finally, for some of the well-known functions, the derivatives are determined using the generalized form. The generalized definition may introduce some simplicity in calculating the derivatives of some of the functions.
Generalized Definition of the Derivative
The classical definition of derivative, which can be traced in any calculus textbook, is
Usually, in calculus textbooks, instead of the parameter
, the more common notation of
h is employed. The term
is the approximate slope of a line passing through points
and
. As
approaches zero, the approximate slope coincides with the exact slope of the function at point
. The following generalization of the derivative expression is proposed in this work for the first time:
where the functions
and
are arbitrary functions of the limiting parameter on the condition that
The generalized definition can be expressed in a more compact form
where
with the functions satisfying (3).
In an interesting video in YouTube (see the website given in the references), the alternative definition of the derivative is discussed in detail.
In our generalized form, the above expression corresponds to the special case of
and with . It is shown in the video that the alternative definition introduces some simplicity in determining the derivatives of some of the well-known functions. The quantum derivative, which is similar to (5), is used by physicists with the expression being without the limiting process (Kunt et al., 2022). Another generalization of the usual derivative is the fractal derivatives in which the derivative operation consists of fractional repetitions rather than integers. See Deppman et al. (2023) for a review of such fractional generalizations. For applications of fractional derivatives to boundary value problems, see He (2020).
Another subcase of the general definition (2) may also be proposed
where the transformation
is indeed a special Lie group of transformations covering scaling and translational transformations as special cases (Pakdemirli & Yürüsoy, 1998).
Error Analysis
If the function is unknown, as in the case of differential equations, usually the approximate form of the derivative is substituted. For example, for the first-order differential equation
the derivative of the classical version is approximated as
and substituted yielding
The above recursive relation is the famous Euler method used in numerical analysis (O’Neil, 1991). The errors introduced by approximate definitions such as (8) are of technical importance. For the classical version given in (1), if
is substituted into (1) without the limit
and the error in the slope is
If , where M is a real number, then the error is of order .
To calculate the error in the generalized version, substitute
to the right-hand side of (4) without taking the limit
and the error is
For , in order not to depend the error on , , that is, for functions , the error depends on x and may become large for large values of x.
For
, the error is from (15):
and hence, the error is of order
. If
, then one can say that the error is of order
in terms of the parameter
. Theoretically speaking, more precise calculations of slope are available in terms of the parameter
if
.
Calculation of the Derivatives
In this section, the derivatives of some of the functions are calculated.
Example 1. The derivative of
is difficult to determine in the classical version
since there are difficulties in evaluating the above limit. Taylor expansions and/or l’Hopital’s rule cannot be used since they require knowledge of the derivative, which is unknown. In the generalized version, if one defines
,
, then the limit is
Using the property
above and simplifying
If one defines
, then the limit is
Hence, it is proven that the derivative of
is
The derivative of is calculated by using the integral definition and differentiating both sides (Thomas & Finney, 1984) or by employing the properties of the exponential function (Strang, 1991) but not directly from (17). According to the generalized definition (18), this task becomes simpler and more straightforward.
Example 2.
To calculate the derivative of the exponential function, take ,
, i.e.,
and the limit can easily be calculated
proving that the derivative of the function is
In the classical definition, one needs two consecutive transformations instead of the one employed above.
The first transformation is
and the second transformation is
, which proves that the limit equals unity and that the derivative of the exponential function is itself.
Example 3.
To calculate the derivative of the hyperbolic sine function from the generalized definition, take
,
, i.e.,
,
Since
, the result is
Proceeding in a similar way, the second limit is
For trigonometric functions, the generalized definition might not introduce simplicities, and the classical definition may be employed in proving the derivatives.
References
- Deppman, A.; Eugenio Megías, E.; Pasechnik, R. Fractal Derivatives, Fractional Derivatives and q-Deformed Calculus. Entropy 2023, 25, 1008. [Google Scholar] [CrossRef] [PubMed]
- He, J.H. A short review on analytical methods for a fully fourth-order nonlinear integral boundary value problem with fractal derivatives. International Journal of Numerical Methods for Heat & Fluid Flow 2020, 30, 4933–4943. [Google Scholar]
- Kunt, M.; Baidar, A.W.; Şanli, Z. Some Quantum Integral Inequalities Based on Left-Right Quantum Integrals. Turkish Journal of Science & Technology 2022, 17, 343–356. [Google Scholar]
- O’Neil, P.V. Advanced Engineering Mathematics; Wadsworth Publishing, Co.: Belmont, California, 1991. [Google Scholar]
- Pakdemirli, M.; Yürüsoy, M. Similarity transformations for partial differential equations. SIAM Review 1998, 40, 96–101. [Google Scholar] [CrossRef]
- Strang, G. Calculus; Wellesley-Cambridge Press: Wellesley, MA, 1991. [Google Scholar]
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https://www.youtube.com/watch?v=XfWgfZ5V2qI&t=13s.
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