1. Introduction and Background
The concept of fractals naturally emerges in the examination of non-linear functions. The fractal theory offers different approaches to describe, quantify, and investigate natural phenomena, such as lightning, rivers, trees, mountains, heart sounds, and so on. One effective approach to creating fractals involves identifying the fixed points of contractive operators within a specific class of Iterated Function Systems (IFSs) [
1].
Constructive approximation theory is based on classical interpolation techniques, which can be substituted by fractal interpolation. This approach is utilized in various domains, including computer graphics, picture compression, and multiwavelets. A fractal set is defined as the graph of a continuous function, and which interpolates a given collection of data, which is known as a fractal interpolation function (FIF). Barnsley presented this concept in 1986 [
2], and it gained popularity through the work of Navascués, Chand, and their respective research groups [
3,
4,
5,
6].
The attractor of a single Iterated Function System is a self-similar fractal, meaning that its local shape is in line with regard to the appropriate contraction maps. When approximating complex curves with non-uniform self-similarity (e.g., simulating stochastic processes such as Brownian motion), it is logical to consider creating fractals with varying levels of structure. Barnsley et al. [
7] examined a collection of infinitely many Iterated Function Systems (IFSs) in order to generate fractals with a variable
T. A
T-variable fractal is a set that, depending on the magnification level, produces at most
T-distinct local patterns at each level. A uniform contractive and uniformly bounded sequence of IFSs is postulated.
By employing the concept of a non-stationary subdivision technique, David and colleagues [
8,
9] recently developed a more generic class of sequences of operators, and investigated their convergence features. The IFS system sequence has been applied to non-stationary subdivision schemes by the authors of [
8]. In doing so, the uniform contractivity constraint that is imposed in the production of
T-variable fractals is relaxed. Furthermore, the freedom to obtain attractors (fractals) with distinct patterns at various dimensions is provided by the employment of various contractive operators.
The investigation of non-stationary fractal functions on support graphs is the primary subject of this paper. As a result of the research conducted by Barnsley [
2] and Levin et al. [
9], Massopust conducted research on non-stationary FIFs in 2019 [
10]. On the one hand, despite the fact that it appears to be natural, and has an extensive range of applications, the utilization of a sequence of IFSs in the aforementioned subjects has received a significantly lower amount of attention. On the other hand, Celik et al. developed the construction of fractal functions on SG in 2008 [
11], and thereafter, its analytic properties are examined by numerous researchers [
12,
13,
14,
15]. Using the Sierpiński gasket, Sahu and Priyadarshi [
15] determined the upper bounds for the box-counting dimension of graphs of harmonic functions and fractal interpolation functions. The study of vector-valued FIFs on SG was conducted by Navascués et al. [
16] in recent times. In addition to demonstrating the smoothness quality of vector-valued FIF on SG, they also launched a systematic approximation theory by making use of the vector-valued FIF on SG.
Our current study is dedicated to the development of the non-stationary FIF on the Sierpiński gasket. There is a significant impact that the parameters of the IFS have on the characteristics and shapes of the FIFs that correspond to them [
5]. The identification of the IFS parameters and the determination of the fractal dimension of the non-stationary FIFs in SG is, therefore, a question that could be considered intriguing. A challenge like the one described above is among the most difficult questions in the field of fractal theory. Determining the exact upper limit of the box-counting and Hausdorff dimension presents an additional challenge that adds to the complexity of the problem that was presented earlier. As part of our recent research [
17], we have conducted an investigation into the dimensional analysis of fractal functions. Additionally, the creation of a non-stationary fractal function in oscillation spaces on SG are covered in this article.
According to David et al. [
9] and Celik et al. [
11], our construction here is based on non-stationary IFS. On the other hand, it is important to mention that the purpose of our work is different. The analysis on SG is the primary focus of our study and, in particular, it connects the theory of analysis on fractals from a theoretical perspective.
The article is structured as follows.
Section 2 begins with a review of the concept of a system of function systems and trajectories.
Section 3 describes how to construct a non-stationary fractal function on SG.
Section 4 presents the results of a thorough examination of the suggested architecture in oscillation spaces, as well as the dimension findings. Finally, we demonstrate in
Section 5 that the suggested fractal functions on SG have finite energy.
3. Non-Stationary Fractal Interpolation Functions on SG
Let
be the vertices of an equilateral triangle on
and
, where
, three contractions of the plane which constitutes an IFS. The Sierpiński gasket (abbreviated as SG) is the attractor of this IFS,
For fix
, consider the iterations
for any sequence
. The union of images of
under these iterations constitutes the set of
-th stage vertex
of
. Let
be a given function. We find an IFS whose attractor is the graph of a continuous function on
, such that
. For
, define maps
by
where
are required to satisfy the following conditions:
and
for every
, where
. For the aforementioned objective, we consider
, where
and
are continuous functions with
and
. Let
. We obtain a sequence of IFSs
.
Theorem 2. Let and be given. The sequence of IFSs defined above produces a continuous function which fulfills .
Proof. First, let
denote the Banach space of real-valued continuous functions
with norm
. Let
; it is obvious that
is a complete space with respect to the metric induced by norm
. For
, a mapping
is defined by
We see that
is a contraction map through the following lines:
It may be observed that the sequence is bounded. By applying Proposition 3, the backward trajectories of converge for every to a unique attractor . This concludes the proof. □
Remark 2. The aforementioned outcome must be examined with [10], Theorem 4. More specifically, [10] Theorem 4 uses the assumption of closed invariant set (see [10], Proposition 3); nevertheless, our proof does not required that assumption. Therefore, our result may be treated as a generalization of [10] Theorem 4. 4. Oscillation Spaces
For
, we define total oscillation of order
by
where
. For
, we consider a new class as
For details related to oscillation spaces, the reader is recommended to refer to [
21].
Let denotes the upper box dimension of A. Then, we have the following result.
Theorem 3. Let be such that . Suppose that . Then, forthere exists a non-stationary fractal function . Furthermore, .
Proof. Let
. We identify that the space
is a closed subspace of
. Since
is a complete metric space [
22] (Theorem 4) with respect to the metric induced by
, it follows that
is a complete metric space with respect to the metric induced by norm
. A sequence of mappings
is defined by
for all
. It is visible that the mapping
is clearly defined. Applying Remark 5 in [
22], for
, we have
Using the hypothesis, we see that
is a contraction map on
. It is visible that the sequence
is bounded. By employing Proposition 3, the backward trajectories
of
converge for every
to a unique attractor
. Since
, we have
by [
23], Theorem
. □
Remark 3. Based on the aforementioned proof, it is evident that each is a contraction and, hence, has a unique fixed point termed as (stationary) FIF, as in [15]. It also fulfills that Now, the functions for are defined by Now, we demonstrate that the graph of the associated stationary fractal function is an attractor of the backward trajectories of IFSs . In the below note, we have mentioned the dimension outcome of a stationary FIF
in the settings of a sequence of IFSs. The proof of this may be obtained using an idea similar to ref. [
2], Theorem 4.
If the sequence of IFSs
as defined earlier fulfills the below given condition
for every
, where
, then
, where
and
are such that
and
, and
is the stationary fractal interpolation function corresponding to the IFS
.
Remark 4. For the sequence of IFSs satisfying the same hypothesis as in Note 1, we believe that the corresponding non-stationary FIF will also have the same bound for the box and Hausdorff dimensions.
To calculate the exact bound for the Hausdorff and box dimensions of the non-stationary FIF, first we can define an open set
, where
denotes interior of the filled triangle ▵ containing SG. It is easy to see that
This, in turn, yields that
for each
. Since
, the IFS
will satisfy the strong open set condition. The proof may be completed using an idea form Theorem
and Theorem
of the work by Graf [
24]. We leave the problem open for the further work in this direction.
Remark 5. Let us write this remark on (stationary) fractal interpolation function. If for all , i.e., all maps are similarity transformation, then by a result of Hutchinson [1], we obtain , where s is a unique solution of . In addition, we have . Using the work of [
25], for
, we consider the space defined by
Then, Verma et al. [
22] Proposition 6 proved that
is a vector space.
Moreover, we have the following result as per [
25], Proposition
.
Lemma 1. Let . Then, Moreover, is a complete metric space, where Theorem 4. Let be such that . Suppose that . Then, forthere exists a non-stationary fractal function . Furthermore,
. Proof. Proof follows from Theorem 3. □
Remark 6. Our above work may be treated as an addendum to the similar works performed in univariate [26] and bivariate [27] settings. 5. Energy
Consider the complete graph
defined on the vertex set
. After constructing graph
with vertex set
for some
, the graph
on
is defined as follows: for any
,
holds if and only if
with
and
. Equivalently,
if and only if there exists
such that
. For
, the graph energies
on
are defined by
Note that the sequence of graph energies
satisfies
, where the minimum is taken over all
, satisfying
for any
, and for any
. After that, for each function
f on
, we identify that
is an increasing sequence. The energy of
f on
is defined as
A function is considered to have finite energy if .
Let us define
. Then, the space
is a Banach space ([
28], Theorem
), where
.
Theorem 5. Let . Let germ function and with . Suppose that . If then .
Proof. Let
. By applying the definition of RB operator
. We have
By employing the definition of energy at
m-th level, for
, we obtain
Further, we write
which shows that each
is coherent under the specified criteria mentioned in the theorem. Now,
Since , each is a contraction mapping.
It is easy to check that the sequence is bounded. Thus, by using Proposition 3, the backward trajectories of converge for every to a unique attractor . Therefore, we have effectively demonstrated the validity of the outcome. □
Remark 7. Since , from the first part of the above proof, we have , provided that and for all .