An investor uses the graphical presentation of Bollinger Bands to get signals of the ups and downs, as well the volatility of the market from the expansion and tightening of the UBB and LBB, reflecting higher and lower volatility. The percent (%) b helps determine the opportunities during extreme periods from the market, looking at the concentration of line graph at the value "0" or "1" reflecting the bearish and bullish trend, respectively. The Bandwidth Index was able to picture out the bullish trend with a squeeze at the upper band. The positive unimodality of Q for NEPSE daily return for the period of the fiscal year 1998–1999 to the fiscal year 2019–2020 indicated normality for the market return. Nevertheless, the results for the trading signals based on the Bollinger bands are seen as useful for an investor by giving a clear signal to "buy" or "sell". At the same time, relying only on Bollinger Bands with a specific period MA, i.e. the Bollinger Bands with a shorter moving average (MA) shows higher fluctuations and vice-versa, hence, could show false signals while choosing inappropriate MA, therefore, help of other technical analysis tools should be taken while going for an investment decision.
Citation: Rashesh Vaidya. NEPSE in Bollinger Bands[J]. National Accounting Review, 2021, 3(4): 439-451. doi: 10.3934/NAR.2021023
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An investor uses the graphical presentation of Bollinger Bands to get signals of the ups and downs, as well the volatility of the market from the expansion and tightening of the UBB and LBB, reflecting higher and lower volatility. The percent (%) b helps determine the opportunities during extreme periods from the market, looking at the concentration of line graph at the value "0" or "1" reflecting the bearish and bullish trend, respectively. The Bandwidth Index was able to picture out the bullish trend with a squeeze at the upper band. The positive unimodality of Q for NEPSE daily return for the period of the fiscal year 1998–1999 to the fiscal year 2019–2020 indicated normality for the market return. Nevertheless, the results for the trading signals based on the Bollinger bands are seen as useful for an investor by giving a clear signal to "buy" or "sell". At the same time, relying only on Bollinger Bands with a specific period MA, i.e. the Bollinger Bands with a shorter moving average (MA) shows higher fluctuations and vice-versa, hence, could show false signals while choosing inappropriate MA, therefore, help of other technical analysis tools should be taken while going for an investment decision.
Let X and Y be two separable metric spaces and let M(X) be the family of compactly supported Borel probability measures on X. We say that μ∈M(X) satisfies the doubling condition if
lim supr↘0(supx∈supp(μ)μ(B(x,ar))μ(B(x,r)))<∞ |
for some a>1 (or, equivalently, any a>1), where B(x,r) is closed ball with a center x and a radius r. We use M0(X) to denote the family of compactly supported Borel probability measures on X that fulfill the doubling condition [1]. To study the multifractal analysis of measures introduced by Mandelbrot in [2,3], we must turn back to the study of sets related to the local behavior of such measures, called level sets, defined, for β∈R, as :
Eμ(β)={x∈supp(μ);limr→0logμ(B(x,r))logr=β}, |
where supp(μ) is the topologic support of μ, and B(x,r) stands for the closed ball with a center x and a radius r>0. Thus, this study is essentially linked to its punctual nature and falls under set theory. However, some geometric sets are essentially known by means of the measures that are supported by them, i.e.,
ν(A)=sup{ν(B), B⊂A}, |
for a given measure ν and a given set A. Hence, when we consider a set A, we focus on the properties of the measure ν rather than the geometric structure of A. The set A is thus partitioned into α-level sets Eμ(β). This allows the inclusion of μ into the computation of the fractal measures and dimensions. Olsen, in [1], introduced the multifractal generalizations of the fractal dimensions. This is achieved by constructing the generalization of Hausdorff and the packing measures, denoted Hq,tμ and Pq,tμ in Rd, where d≥1, respectively. Later, in [4], the authors introduced a new multifractal formalism that deviates from the classical approach. To achieve this, they constructed two distinct measures known as the lower and upper Hewitt-Stromberg (H-S) measures, denoted, respectively, by Hq,tμ and Pq,tμ. These measures serve as fundamental tools in the analysis of multifractal structures. Given the importance of these measures in this study, it is crucial to examine their properties, including their behavior on product sets and their density characteristics both of which play a critical role in understanding the broader implications of this new formalism. In particular, in [5], the author proved the existence of a constant c>0 such that, for any measurable sets A⊆Rd and B⊆Rl, the following inequality holds:
Hq,s+tμ×ν(A×B)≤c1Hq,sμ(A)Hq,tν(B)≤c2Pq,s+tμ×ν(A×B)≤c3Pq,sμ(A)Pq,tν(B), | (1.1) |
provided that we have the measures μ∈M0(Rd) and ν∈M0(Rl) and with the convention that
0×∞=0. |
The constant ci (i=1,2,3) depends only on certain structural parameters, such as the dimensions d and l, but is independent of the specific choice of E and F. Moreover, in the specific case q=0, the associated dimensional inequalities for the products of these measures have been derived in [6,7,8]. For additional related discussions, the readers may consult [9,10]. Furthermore, the inequalities above are explicitly stated in this case in [8,11,12,13]. In particular, if
d=l=1andμ=ν |
are basically the Lebesgue measure on R, one has, for
q+s=q+t=log2/log3 |
and E=F as the middle third Cantor [14,15]
Hq,sμ(A)Pq,tμ(B)=1×4t<Pq,s+tμ×ν(A×B)=4s+t=Pq,sμ(A)Pq,tν(B). |
Remark 1. The equation of (1.1) has important physical interpretations depending on the context. Note, for q=0, that
H1=L1, |
is the one-dimensional Lebesgue measure. In particular, if A,B⊆R, then the product set A×B forms a subset of R2, and then (1.1) gives an approximation of the Hausdorff measure of A×B using the area of the region covered by the Cartesian product. These prove, in particular, that
H2(A×B)≠H1(A)H1(B). |
A Hausdorff function
h:R+→R+ |
is a function that is increasing, continuous, and satisfies
h(0)=0. |
These functions are often used in the context of geometric measure theory, particularly in defining Hausdorff measures. Let F denote the set of all such dimension functions, i.e., the set of all Hausdorff functions. Additionally, a Hausdorff function h is considered to fulfill the doubling condition if a positive constant γ exists such that the following inequality holds:
h(2r)≤γh(r), for all r>0. |
This condition essentially ensures that h does not grow too quickly and is often used to ensure specific regularity properties of the corresponding measures. The subset of F consisting of all Hausdorff functions that satisfy the doubling condition is denoted by F0. Recently, in [16], the authors introduced the generalized pseudo-packing measure Rq,hμ and they proved that
Hq,hgμ×ν(A×B)≤Hq,hμ(A)Rq,gν(B)≤Rq,hgμ×ν(A×B), | (1.2) |
for all A⊆X and B⊆Y, provided that we do not have 0–∞ case; that is, the product on the medium side does not take the form 0×∞ or ∞×0. Note that we do not any restriction on the measures μ,ν,h, and g; that is, they do not satisfy necessary the doubling condition. In addition, one has (see again [16])
Pq,hgμ×ν(A×B)≤Qq,hμ(A)Pq,gν(B), | (1.3) |
except in the 0–∞ case, where Qq,hμ is the weighted generalized packing measure. In particular, one can obtain (1.1) under appropriate geometric conditions on X and Y (amenable to packing) [8,16].
Traditional packing and Hausdorff measures are defined using packings and coverings made up of collections of balls with diameters less than a given positive value δ. An alternative approach to constructing fractal measures utilizes packings and coverings by using families of balls with a fixed diameter δ. These measures, known as H-S measures, were first introduced in [17, Exercise (10.51)]. They were later explicitly described in Pesin's monograph [18] and are also referenced, albeit in an implicit manner, in foundational works such as Mattila's [19]. The importance of H-S measures goes beyond their theoretical definition; they offer a flexible framework for analyzing fractals and their complex characteristics. Numerous studies, including [20,21,22,23] for H-S measures and [24,25,26] for Standard measures, have demonstrated their utility in exploring the local properties of fractals and the behavior of fractal products. These works underscore the adaptability of H-S measures across various contexts, thus enriching the field of fractal geometry and its applications. Furthermore, Edgar's comprehensive exposition of these measures [27, pp. 32–36] provides a clear and accessible introduction, thoroughly detailing their construction, properties, and potential applications.
In Section 3, we are interested in studying the counterpart of the formula (1.1) related to the lower and upper H-S measures in Euclidean space. This result was shown for q=0 in [28] in Euclidean space. We will prove the following theorem.
Theorem 1. Let A⊆Rd, B⊆Rl, μ∈M0(Rd), ν∈M0(Rl), h,g∈F0 and q∈R. Positive constants c1–c4 exist such that
Hq,hμ(A)Hq,gν(B)≤c1Hq,hgμ×ν(A×B)≤c2Hq,hμ(A)Pq,gν(B)≤c3Pq,hgμ×ν(A×B)≤c4Pq,hμ(A)Pq,gν(B), | (1.4) |
except in the 0–∞ case.
To prove the first inequality, we introduce a new multifractal measure that parallels the lower H-S measure and is notably simpler to analyze. This is achieved by utilizing a class of half-open dyadic cubes as covering sets in the definition, instead of using closed balls. The use of half-open dyadic cubes provides a new framework for the analysis, simplifying the structure of the measure. For the second inequality, we extend the technique by replacing the traditional dyadic cubes with half-open semi-dyadic cubes. This adjustment leads to the definition of two distinct measures that correspond to the upper and lower H-S measures. This choice arises from the fact that semi-dyadic cubes vn(x) are less sensitive to the position of x compared with the corresponding dyadic cubes un(x). Semi-dyadic cubes have been utilized in works such as [5,13,29]. It is important to note that this construction is specific to Euclidean space, making our proof distinct from those in [30].
Remark 2. It is important to emphasize that our analysis was not conducted for an arbitrary subset Γ⊂R2, but specifically for cases where Γ takes the form of a Cartesian product
Γ=A×B. |
Addressing such a problem is far from straightforward, as it necessitates the application of integral versions of product set. For a deeper exploration of these techniques and their implications, we refer the reader to [5,31,32].
When
h(r)=rt, |
the measures Hq,hμ and Pq,hμ are simply denoted as Hq,tμ and Pq,tμ, respectively. In this case, these measures assign, in the standard manner, a multifractal dimension to each subset A of Rd, defined as follows:
bqμ(A)=inf{t∈R,Hq,tμ(A)=∞}andBqμ(A)=inf{t∈R,Pq,tμ(A)=∞}. |
If q=0, bμ(A) and Bμ(A) do not depend on μ and are simply denoted b and B, respectively. Theorem A implies, when all the hypothesis are satisfied, that
bqμ1(A)+bqμ2(B)≤bqμ1×μ2(A×B)≤bqμ1(A)+Bqμ2(B)≤Bqμ1×μ2(A×B). | (1.5) |
Moreover, all these inequalities may be strict. Indeed, one can construct two sets A and B such that
bqμ1(A)+bqμ2(B)<bqμ1×μ2(A×B), |
(see [33] for q=0). However, in Example 2, we give a sufficient condition to get the first equality in Eq (1.5):
bqμ1(A)+bqμ2(B)=bqμ1×μ2(A×B). |
One can define also the multifractal separator functions
bμ(q)=bqμ(supp(μ)) |
and
Bμ(q)=Bqμ(supp(μ)). |
Where bμ is known to be a decreasing function, while Bμ is both a decreasing and convex function [4]. In addition, it holds that
bμ≤Bμ. |
As a consequence, since
supp(μ1×μ2)=supp(μ1)×supp(μ2), |
we get the following result:
bμ1(q)+bμ2(q)≤bμ1×μ2(q)≤bμ1(q)+Bμ2(q)≤Bμ1×μ2(q), | (1.6) |
by taking
E=supp(μ1) |
and
F=supp(μ2) |
in Theorem 1. Similar results were also proven for the s-dimensional Hausdorff measure Hs and the s-dimensional packing measure Ps [6,13,34,35]. In addition, a variety of related results and further developments on this problem can be found in the works of [36,37].
Now, given μ,θ∈P(Rd), q∈R, h,g∈F0, and x∈supp(μ), we define the upper and lower (q,s)-densities of θ at x with respect to μ as
¯dq,hμ(x,θ)=lim supr→0θ(B(x,r))μ(B(x,r))qh(2r) and d_q,hμ(x,θ)=lim infr→0θ(B(x,r))μ(B(x,r))qh(2r). | (1.7) |
If
d_q,hμ(x,θ)=¯dq,hμ(x,θ), |
we use dq,hμ(x,θ) to denote the common value. In [30], the authors used some density inequalities as "local versions" of the product inequalities. In particular, they proved that the inequality
Pq,hgμ×ν(A×B)≤cPq,hμ(A)Pq,gν(B) |
may be deduced from the following density inequality:
cd_q,hgμ×ν((x,y),θ1×θ2)≥d_q,hμ(x,θ1)d_q,gν(y,θ2), |
where θ1 is the restriction of Pq,hμ to E and θ2 is the restriction of Pq,gν to B.
The set A satisfies the condition
bqμ(A)=Bqμ(A) |
for measures μ under consideration, which will be called regular set. Regularity is defined with respect to various measures, such as the packing measure [29,38], the Hausdorff measure [39,40,41,42], and the H-S measure [43,44,45]. Notably, Tricot et al. [38,46] demonstrated that a subset A of Rd has integer Hausdorff and packing dimensions if it is strongly regular, meaning that
Ht(A)=Pt(A) |
for t≥0. Furthermore, as a consequence of (1.5), it follows that if either E or F is regular, then
bqμ1(A)+bqμ2(B)=bqμ1×μ2(A×B)=Bqμ1×μ2(A×B). | (1.8) |
In Theorem 1, we assume that the products do not take the form 0×∞ or ∞×0. In Section 4, by estimating the measure of d-dimensional symmetric generalized Cantor sets, we demonstrate that this assumption is essential and can not be omitted. Specifically, let 0<α,β<1, to establish the second inequality in (1.4), we then need to prove that
¯Hq,α+βμ×ν,0(H)≤c¯Hq,αμ,0(A)¯Pq,βν(B), |
for all
H⊆A×B |
and some positive constant c, where ¯Hq,αμ,0 and ¯Pq,βν are the pre-lower and pre-upper H-S measures, respectively (see Section 3.2 and Eq (3.2)). We establish the following result.
Theorem 2. One-dimensional generalized Cantor sets K1, K12, K22, and K32 such that
¯Hq,αμ,0(K1)=0,¯Pq,βμ(Kj2)=∞, |
and ¯Hq,α+βμ×ν,0(K1×K2) and ¯Pq,α+βμ×ν(K1×K2) are infinite, positive finite, and zero according as j=1,2,3, respectively.
In this paper, we use formulas containing too many different variables, which is unpleasant, and omitting these extra parameters will create no confusion. To this end, for μ∈P(Rd),ν∈P(Rl), and h,g∈F, we define the gauge functions ξ and ζ as
ξ(x,r)=μ(B(x,r)qh(2r)andζ(x,r)=ν(B(x,r)qg(2r), | (2.1) |
where q∈R, r>0, with the conventions
0q=∞ |
for q≤0 and
0q=0 |
for q>0. The reader should note that we have simply used ξ (respectively, ζ) to denote the gauge function depending on μ (respectively, ν), q, and h (respectively, g). If
h(r)=rsandg(r)=rt |
for s,t∈R, then ξ and ζ will be denoted as ξs and ζt respectively. In this section, we construct the different fractal measures used in this paper. Let δ>0,
A⊆supp(μ), |
and {B(xi,ri)}i is a δ-packing of the A, that is, a countable family of disjoint closed balls such that xi∈A and
0<2ri<δ |
for all i. Write
Pξδ(A)=sup∑ξ(xi,ri)andPξ0(A)=infδ>0Pξδ(A), |
where the supremum is taken over all δ-packings of the set E. The generalized packing measure Pξ of A with respect to ξ is defined by
Pξ(A)=infA⊆⋃iAi∑Pξ0(Ai) |
and
Pξ(∅)=0. |
In a similar way, we define
Hξδ(A)=inf∑ξ(xi,ri)andHξ0(A)=supδ>0Hξδ(A), |
where the infimum is taken over all δ-coverings {B(xi,ri)}i of E; that is, xi∈E, 0<2ri<δ, and
A⊆⋃iB(xi,ri). |
We define the generalized Hausdorff measure as
Hξ(A)=supE⊆AHξ0(E) |
and
Hξ(∅)=0. |
We refer to [1,5] for more details (see also [46,47] for q=0). Moreover, an integer κ∈N exists such that
Hξ≤κPξ. |
Similarly, we define
¯Pξ(A)=lim supr→0Mqμ,r(A)h(2r), |
where
Mqμ,r(A)=sup{∑iμ(B(xi,r))q|{B(xi,r)}iis a centered packing ofA}. |
It is clear that ¯Pξ is increasing and
¯Pξ(∅)=0. |
However it is not σ-additive. For this, we define the Pξ-measure defined as
Pξ(A)=inf{∑i¯Pξ(Ai)|A⊆⋃iAiand theA′is are bounded}. |
In a similar way, we define
¯Hξr(A)=Nqμ,r(A)h(2r)and¯Hξ0(A)=lim infr→0¯Hξr(A), |
where
Nqμ,r(A)=inf{∑iμ(B(xi,r))q|{B(xi,r)}iis a centered covering ofA}. |
Clearly, ¯Hξ0 is not countably subadditive and not increasing; one needs some modification to obtain an outer measure. More precisely, let
¯Hξ(A)=inf{∑i¯Hξ0(Ai)|A⊆⋃iAiand theA′is are bounded} |
and
Hξ(A)=supE⊆A¯Hξ(E). |
It is well known (see, for instance, [48]) that Hξ and Pξ are metric outer measures, which implies that they are measures on the Borel algebra. Moreover, for some integer κ∈N, the following inequality holds:
Hξ(A)≤Hξ(A)≤κPξ(A)≤κPξ(A). |
In the following, we recall the construction of the one-dimensional generalized Cantor set K. Let L be a positive number, let {nk}k≥1 be a sequence of integers, and let {λk}k≥1 be a sequence of positive numbers such that
nk>1, n1λ1<L and λk+1nk+1<λk | (2.2) |
for all k≥1. The construction of the generalized Cantor set {L,{nk}k≥1,{λk}k≥1} is as follows. In the first step, from a given closed interval with the length L, remove (n1−1) open intervals and then leaves n1 closed intervals with the length λ1, denoted by I1,…,In1. Let
J1=n1⋃j1=1Ij1. |
In the second step, from each remaining closed interval with the length λ1, remove (n2−1) open intervals and leaves n2 closed intervals with the length λ2. These are denoted as Ij1,j2, and we can write
J2=n1⋃j1=1n2⋃j2=1Ij1,j2. |
We continue this process and, in the k-th step, obtain n1n2⋯nk closed intervals with the length λk, denoted Ij1,j2,…,jk and denote their union as Jk. Then let
K=∞⋂k=0Jk. |
Let
μ=ν |
be the uniform measure on K, that is
μ(Qk)=λk |
and define
Sk=μ(Qk+1)μ(Qk)=λk+1λk. | (2.3) |
This construction can be generalized in Rd and Kd, denoting the generalized Cantor set. Let Fk be the product set of d copies Jk. Thus, Fk is the union of (n1n2…nk)d closed cubes with the side λk, each of which may be denoted as Q(k), and
Kd=∞⋂k=0Fk. |
The next lemma will be used in Section 4 to estimate the measure of Kd.
Lemma 1. Let Kd be the d-dimensional symmetric generalized Cantor set (d≥1). A set function Ψ, defined on every non-empty closed subset in Rd and r0, exists such that, for every open cube I with the side r≤r0, we have
Ψ(I)≤23dh(r)λqk, | (2.4) |
where k is the unique integer such that
λk+1≤r<λk. |
Proof. We start the proof by constructing the set function Ψ. Assume that
lim infk→∞(n1n2…nk)dh(λk)λqk>0. |
Let
0<b<lim infk→∞(n1n2…nk)dh(λk)λqk, |
then there is a k0 such that
λk0<t0 |
and
h(λk)>b/(n1n2…nk)dλqk |
for all k>k0. We define the sequence (λ′k) such that
h(λ′k)=b(n1n2…nk)dλqk. | (2.5) |
Clearly, we have λk>λ′k (since h is increasing) and
h(λ′k+1)=b(n1n2…nk+1)dλqk+1=(2.3)b(n1n2…nk+1)dSqkλqk=h(λ′k)ndk+1Sqk. |
Let A be any open set and define
Nqμ,k(A)=inf{∑iμ(Qi)q,Qi∈Fk,and meeting A}. |
Then, we have
Nqμ,k+1(A)=inf{∑iμ(Qi)q,Qi∈Fk+1,and meeting A}≤inf{∑iμ(Qi)qμ(Qk)qμ(Qk)qQi∈Fk+1,and meeting A}≤kdk+1Sqkinf{∑iμ(Qi)q,Qi∈Fk,and meeting A}=kdk+1SqkNqμ,k(A). |
It follows that the sequence {Nqμ,k(A)h(λ′k)} is decreasing, and we may define the function
Ψ(A)=limk→0Nqμ,k(A)h(λ′k). |
Now, we will prove (2.4). Let I be an open cube, k exists such that
1≤j≤nk+1andλk+1≤r<λk. |
Moreover, take a positive sequence (δk)k≥1 such that
nkλk+(nk−1)δk=λk−1. | (2.6) |
Then the following exists:
1≤j≤nk+1, |
such that
jλk+1+(j−1)δk+1≤r<(j+1)λk+1+jδk+1. | (2.7) |
Observe that
Nqμ,k+1(I)=inf{∑iμ(Qi)q,Qi∈Fk+1,and meetingA}≤2d(j+1)dμ(Qk+1)q≤22djdμ(Qk+1)q. |
It follows that
Ψ(I)≤22djdμ(Qk+1)qh(λ′k+1), |
● If j=1, then
Ψ(I)≤22dμ(Qk+1)qh(λk+1)≤22dμ(Qk+1)qh(r); |
● If 1<j<nk+1, then
jdμ(Qk+1)qh(λ′k+1)=(2.5)jdμ(Qk+1)qb(n1n2…nk+1)=(j/n1n2…nk+1)db=(j/nk+1)dh(λ′k)μ(Qk)q. |
Since
λ′kjkr+1≤λ′k, |
and
t↦h(t)/td |
is decreasing, we get
(j/nk+1)dh(λ′k)≤h(jλ′k/nk+1), |
and then
jdμ(Qk+1)qh(λ′k+1)≤μ(Qk)qh(jλ′k/nk+1). |
Now, observe that
jλ′k/nk+1≤jλk/nk+1≤(2.6)jnk+1nk+1(λk+1+δk+1)≤2(jλk+1+(j−1)δk+1)≤(2.7)2r. |
As a consequence, we obtain
Ψ(I)≤22djdμ(Qk+1)qh(λ′k+1)≤22dμ(Qk)qh(2r)≤23dμ(Qk)qh(r). |
This completes the proof.
We set, for n∈N,
Un={d∏i=1[li2n,li+12n[,l1,…,ld∈Z} |
and
Vn={d∏i=1[12li2n,12li+12n[,l1,…,ld∈Z}. |
The family Un denotes the set of half-open dyadic cubes of order n. For x∈Rd, let un(x) denote the unique cube u∈Un that contains x. Similarly, the family Vn consists of half-open dyadic semi-cubes of order n. For x∈Rd, let vn(x) represent the unique semi-cube v∈Vn that contains x and has its complement at a distance of 2−n−2 from un+2(x). Define
K={(k1,…,kd)∣ki=0 or 12}. |
For each
k=(k1,…,kd)∈K, |
let
Vk,n={d∏i=1[ki+li2n,ki+li+12n[,l1,…,ld∈Z}. |
Note that for
v≠v′∈Vk,n, |
we have
v∩v′=∅. |
Additionally, the collection (Vk,n)k∈K forms a partition of the family Vn. Moreover, if
v,v′∈Vk:=⋃n≥0Vk,n, |
then either
v∩v′=∅ |
or one is contained within the other. Finally, for A⊂Rd, define
Vn(A)={vn(x):x∈A}andVk,n(A)=Vn(A)∩Vk,n. |
In what follows, we construct measures on Rd analogous to the generalized lower and upper H-S measures. However, instead of using the collection of all closed balls in the definition, we employ the class of all half-open dyadic semi-cubes. For A⊆Rd, we define
¯H∗ξ(A)=lim infn→+∞N∗qμ,n(A)h(2−n)and¯P∗ξ(A)=lim supn→+∞M∗qμ,n(A)h(2−n), |
where the numbers N∗n(A) and M∗n(A) are defined as
N∗qμ,n(A)=inf{∑iμ(vi)q|(vi)i∈Iis a family of coverings ofAsuch that vi∈Vn(A)} |
and
M∗qμ,n(A)=sup{∑iμ(vi)qvi∈Vn(A),i∈I,and¯vi∩¯vj=∅for i≠j}. |
The functions ¯H∗ξ and ¯P∗ξ are increasing and satisfy
¯H∗ξ(∅)=¯P∗ξ(∅)=0. |
However these functions are not σ-additive. For this, we consider
H∗ξ(A)=inf{∑i¯H∗ξ(Ai)|A⊆⋃iAiAiis bounded}, |
P∗ξ(A)=inf{∑i¯P∗ξ(Ai)|A⊆⋃iAiAiis bounded}. |
Lemma 2. For every set A⊂Rd, a constant c>0 exists such that
c−1Pξ(A)≤P∗ξ(A)≤cPξ(A)andc−1Hξ(A)≤H∗ξ(A)≤cHξ(A). | (3.1) |
Proof. This arises from the fact that
B(x,2−n−2)⊆vn(x)⊆B(x,√d2−n). |
This completes the proof.
Similarly, we may define H∗∗ξ and P∗∗ξ, by using the class of all half-open dyadic cubes in the definition instead of the class of all half-open dyadic semi-cubes. However, it is important to note the resulting pre-measure, denoted ¯P∗∗ξ, is not equivalent to the pre-measure ¯Pξ. For more discussion, consult [29, Example 3.5], where the interplay between the two pre-measures is explored. This highlights how seemingly minor changes in the class of sets used can lead to significant differences in the resulting pre-measures and their properties.
In this section, for the sake of simplicity and clarity, we focus on results that pertain specifically to subsets of the plane. However, it is worth noting that these results can be extended to higher-dimensional spaces without significant complications. Let Π⊂R2 represent a subset of the plane. For a given x-coordinate, we use Πx to denote the set of all points in Π whose abscissa (x-coordinate) equals x. Given an arbitrary subset A of the x-axis, we will only prove that, if x∈A, we have
Hζ(Πx)>a |
or some constant a, and then
¯Hξζ(Π)≥ΠaHξ(A). |
Let n be a non-negative integer and let {Ii×Ij}i,j be a collection of half-open dyadic cubes of order n covering Π. Set
An={x∈E,N∗∗qν,n(Πx)g(2−n)>b−11a}. |
Note that
N∗∗qμ×ν,n(Π)h(2−n)g(2−n)≥N∗∗qμ,n(An)inf{N∗∗qν,n(Πx),x∈An}h(2−n)g(2−n)≥b−11aN∗∗qμ,n(An)h(2−n). |
This holds for any covering of Π by the binary squares {Ii×Ij}i,j with 2−n sides. Hence,
b−11a¯H∗ξn(An)≤¯H∗ξζn(Π)≤¯H∗ξζ(Π). |
Since An increases to A as n→+∞, then for any p≤n, we have
b−11a¯H∗ξn(Ap)≤b−11a¯H∗ξn(Ak)≤¯H∗ξζ(Π). |
Thus, we obtain
b−11aH∗ξn(Ap)≤b−11a¯H∗ξn(Ep)≤¯H∗q,hgμ×ν(Π)≤α1¯Hq,hgμ×ν(Π) |
for p≥1. Thereby, the continuity of the measure H∗ implies that
b−11aH∗ξ(A)≤α1¯Hq,hgμ×ν(Π). |
Thus, using Lemma 2, we get
b−21aHξ(A)≤b−11aH∗q,hμ(A)≤α1¯Hξζ(Π). |
Finally, by taking
Π=b−21α−11, |
we get the result.
Let A⊆Rd and B⊆Rl. We prove that a constant c>0 exists such that
Hξζ(A×B)≤cHξ(A)Pζ(B). |
Let
H⊆A×B, |
r>0, and let {B(xi,r)}i be a centered r-covering of A. We denote n as the integer such that
√l2−n<r≤√l2−n+1. |
For v∈Vn(B) with
(B(xi,r)×v)∩H)≠∅ |
and each i, choose a point
yi,v∈B(xi,r) |
and a point y′i,v∈v such that
(yi,v,y′i,v)∈(B(xi,r)×v)∩H). |
Note that
H⊆⋃i(⋃v∈Vn(B)(B(xi,r)×v)∩H≠∅B(xi,r)×v)⊆⋃i(⋃v∈Vn(B)(B(xi,r)×v)∩H≠∅B(yi,v,2r)×B(y′i,v,2r))⊆⋃i(⋃v∈Vn(B)(B(xi,r)×v)∩H≠∅B((yi,v,y′i,v),2r)). |
As a consequence, we have the family (B((yi,v,y′i,v),2r))i∈N,v∈Vn(B),B(xi,r)×v)∩H≠∅, which forms a centered (2r)-covering of H. Furthermore, we get
B(y′i,v,ηr)⊆B(y′i,v,2−n−2) |
for
ηr=2−3√lr. |
It follows, for each k∈K, that the family
(B(y′i,v,ηr),i∈N,v∈Vk,n(B),B(xi,r)×v)∩H≠∅ |
is a centered ηr-packing of B. It follows that
¯Hξζ2r(H)≤∑i(∑v∈Vn(B)(B(xi,r)×v)∩H≠∅μ(B(yi,v,2r))qν(y′i,v,2r)qh(4r)g(4r))≤mhmgmqν∑iμ(B(yi,v,2r))qh(2r)(∑k∈K∑v∈Vk,n(B)(B(xi,r)×v)∩H≠∅ν(y′i,v,ηr)qg(2ηr))≤mhmgmqν∑iμ(B(yi,v,2r))qh(2r)(∑k∈K¯Pζηr(B))≤2lmhmgmqν¯Pζηr(B)∑iμ(B(yi,v,2r))qh(2r). |
Thus, by considering the infimum over all possible centered r-coverings of the set A, we get
¯Hξζ2r(H)≤2lmhmgmqν¯Hξr(A)¯Pζηr(B). |
Therefore,
¯Hξζ0(H)≤clim infr→0¯Hξr(A)lim supr→0¯Pζηr(B)=c¯Hξ0(A)¯Pζ(B), | (3.2) |
where
c=2lmhmgmqν. |
Now, assume that
A⊆⋃iAi |
and
B⊆⋃jBj. |
Then
H⊆A×B⊆⋃i,jAi×Bj. |
It follows that
¯Hξζ(H)≤∑i,j¯Hq,hgμ×ν,0(Ai×Bj)≤c∑i,j¯Hq,hμ,0(Ai)¯Pq,gν(Bj).≤c(∑i¯Hξ0(Ai))(∑j¯Pζ(Bj)). |
Since the cover (Ai) of A and the cover (Bj) of B were arbitrarily chosen, we obtain
¯Hξζ(H)≤c¯Hξ(A)Pζ(B)≤cHξ(A)Pζ(B). |
This holds for all for all
H⊆A×B |
which implies that
Hξζ(A×B)≤cHξ(A)Pζ(B). |
Let
A⊆RdandB⊆Rl. |
We aim to show that a constant c>0 exists such that the following inequality holds:
Pξζ(A×B)≥cHξ(A)Pζ(B). |
For simplicity, we limit our discussion to subsets of the plane, although the result can be extended to higher dimensions without without significant complications. Let Q be any packing of B consisting of semi-dyadic intervals, and let C be any covering of A composed of semi-dyadic intervals. We define the following
C1={ui∈C,uiis dyadic and¯ui∩¯uj=∅fori≠j},C2={ui∈C,uiis not dyadic and¯ui∩¯uj=∅fori≠j},C3={ui∈C,uiis dyadic}⋂C∖C1,C4={ui∈C,uiis not dyadic}⋂C∖C2. |
Clearly, we have each of Ci is a packing of E and Ci×Q is a packing of A×B. Therefore,
4M∗q,hgμ×ν,n(A×B)h(2−n)g(2−n)≥∑u∈Qν(u)qh(2−n)g(2−n)(∑v∈C1μ(v)q+∑v∈C2μ(v)q+∑v∈C3μ(v)q+∑v∈C4μ(v)q). |
This holds for any packing Q of B and
C=⋃iCi, |
so we have
4M∗q,hgμ×ν,n(A×B)h(2−n)g(2−n)≥M∗q,gν,n(B)g(2−n)∑v∈Cμ(v)qh(2−n)≥M∗q,gν,n(B)g(2−n)N∗q,hμ,n(A)h(2−n). |
Thus,
¯P∗ξζ(A×B)≥14¯P∗ζ(B)¯H∗ξ(A)≥14P∗ζ(B)H∗ξ(A). |
Finally, we get the desired result using (3.1).
Let A⊆Rd and B⊆Rl. We will prove that a constant c>0 exists such that
P∗ξζ(A×B)≤cP∗ξ(A)P∗ζ(B). |
Here again, we limit our study to subsets of the plane, since the extension to higher dimensions does not involve significant complications. Let B represent any packing of the set A×B containing semi-dyadic squares, where each square is formed as the Cartesian product of two semi-dyadic intervals. We define the sets as follows:
C={un(x):∃vn(y)such that wn(x,y)=un(x)×vn(y)∈B,x∈A,y∈B} |
and
Q={vn(x):∃un(y)such that wn(x,y)=un(x)×vn(y)∈B,x∈A,y∈B}. |
Next, we examine the subclasses
C1={un(x)∈C,un(x)is dyadic},Q1={vn(x)∈Q,vn(x)is dyadic},C2={un(x)∈C,un(x)is not dyadic},Q2={vn(x)∈Q,vn(x)is not dyadic}. |
It is not difficult to note that each of C1,C2 is a packing of A and, similarly, each of Q1, Q2 is a packing of B. Moreover, each square of the packing B is in the collection Ci×Qj, i,j∈{1,2}. Therefore,
∑(u,v)∈Bμ(u)qν(v)qh(2−n)g(2−n)≤[∑u∈C1μ(u)qh(2−n)+∑u∈C2μ(u)qh(2−n)]⋅[∑v∈Q1ν(u)qg(2−n)+∑v∈Q2ν(u)qg(2−n)]≤4M∗q,hμ,n(A)h(2−n)M∗q,gν,n(B)g(2−n). |
This holds, for any packing of A×B, so we have
M∗q,hgμ×ν,n(A×B)h(2−n)g(2−n)≤4M∗q,hμ,n(A)h(2−n)M∗q,gν,n(B)g(2−n) |
and then
¯P∗ξζ(A×B)≤4¯P∗ξn(A)¯P∗ζn(B). |
Let
A⊆⋃iAi |
for
B⊆⋃jBj, |
we have:
P∗ξζ(A×B)≤∑i,j¯P∗ξζ(Ai×Bj)≤4∑i,j¯P∗ξ(Ai)¯P∗ζ(Bj).≤4(∑i¯P∗ξ(Ai))(∑j¯P∗ζ(Bj)). |
Since (Ai) represents an arbitrary covering of E and (Bj) represents an arbitrary covering of B, we can deduce that
P∗ξζ(A×B)≤4P∗ξ(A)P∗ζ(B). |
Finally, by applying (3.1), we obtain the desired conclusion.
Let μ,θ∈M(Rd), q,s,t∈R, and x∈supp(μ), and recall the upper and lower (q,h)-densities of θ at x with respect to μ as defined in (1.7). In this section, we assume that
Pξs(A)<∞ |
and
Pζt(B)<∞. |
When studying fractal measures, a common question that naturally arises is whether we can guarantee the existence of subsets that possess finite or positive Hausdorff measures. This question becomes crucial in understanding the intricate structure of fractals, as it involves determining whether certain subsets exhibit measurable properties in terms of the Hausdorff measure, either finite or positive. Assume that
inf0<r≤δqlnμ(B(x,r)+sln(2r)lnδ≤−αandinf0<r≤δqlnν(B(x,r)+tln(2r)lnδ≤−α | (3.3) |
for some positive real number α. The assumption (3.3) implies, for every δ>0 that is small enough, that
μ(B(x,r))qν(B(x,r))q(2r)t+s≥δ−2α. |
It follows that for
G={x}×{y}, δ>0, |
we then have
¯Hq,s+tμ×ν,2δ(G)≥(2δ)−2α. |
Letting δ tend to zero, we get
Hξsζt({G})≥Hξsζt({G})=¯Hξsζt({G})=+∞. |
Note that the assumption (3.3) is satisfied; for instance, if we take
μ=ν |
to be the Lebesgue measure with
q+t<0. |
In this case, we see that the Hausdorff measure constructed above is the standard Hausdorff measure Hφ with
φ(r)=(2r)q+t. |
Thus, for any closed nonempty set
G⊆A×B, |
every subset of G, including the empty set, is a subset of infinite measures. Thus, we may construct the measures Hξsζt for which the subset of finite measure properties can fail to hold for every closed set of infinite measures. One can assume also that for every δ>0, the following exists:
0<r≤δ/2, |
such that
μ(B(x,r))q(2r)t≤δ. |
Using Theorem 1, we formulate a sufficient condition to obtain
0≤Hξsζt(G)≤Pξsζt(G)<∞. |
First, we will state the following result, which is a direct consequence of Theorem 1.
Corollary 1. Let A⊂Rd and B⊂Rl, μ,θ∈P(Rd), and ν,θ′∈P(Rl) such that μ and ν satisfy the doubling condition. Let
G′⊂G⊆A×B, |
such that
Hq,s+tμ×ν(G)=∞. |
(1) Assume that if inf(x,y)∈G′d_q,hsμ(x,θ)<∞ and inf(x,y)∈G′d_q,htν(x,θ′)>0, then Pξsζt(G′)<∞.
(2) Assume that if sup(x,y)∈G′¯dq,hsμ(x,θ)<∞ and sup(x,y)∈G′¯dq,htν(x,θ′)>0, then Hξsζt(G′)>0.
Proof. Using [30, Lemma 3], we have
Hξs(A)≥γθ(A) |
if
supx∈A¯dq,hsμ(x,θ)<∞ |
and
Pξs(A)≤˜γθ(A), |
whenever
infx∈Ad_q,hsμ(x,θ)>0, |
where γ,˜γ are positive constants. for all θ∈P(Rd). Thus, the result follows from Theorem 1.
Example 1. Recall the construction of the Moran set given in Section 2.2.
Lemma 3. [49] Let A⊂I be a Moran set that satisfies the strong separation condition, and let θ be a finite Borel measure with
supp(θ)⊂A. |
Then there are some positive constants ci (1≤i≤4) depending on δ and t, such that the following inequalities hold for any φ(i)∈A:
c1lim_n→∞θ(In(i))μ(In(i))q|In(i)|t≤lim_r→0θ(B(φ(i),r))μ(B(φ(i),r))q(2r)t≤c2lim_n→∞θ(In(i))μ(In(i))q|In(i)|t,c3¯limn→∞θ(In(i))μ(In(i))q|In(i)|t≤¯limr→0θ(B(φ(i),r))μ(B(φ(i),r))q(2r)t≤c4¯limn→∞θ(In(i))μ(In(i))q|In(i)|t. |
Now consider the special case I=[0,1], nk=2, and ckj=13 for all k≥1 and 1≤j≤nk. In this case, the Moran set A=B is the classical ternary Cantor set. Let
α=log2log3 |
and θ and θ′ be probability measures on I defined by
θ(In(i))={|In(i)|α,ifi∈D,0,otherwise,θ′(In(i))={|In(i)|β,ifi∈D,0,otherwise, |
where
α=q+sandβ=q+t. |
It is clear that
supp(θ)⊂Eandsupp(θ)′⊂E. |
Moreover, we have
limn→∞θ(In(i))μ(In(i))q|In(i)|s=1andlimn→∞θ′(In(i))μ(In(i))q|In(i)|t=1. |
It follows, using Lemma 3, that
0<d_q,hsμ(x,θ)≤¯dq,hsμ(x,θ)<∞ |
and
0<d_q,htν(x,θ)≤¯dq,htν(x,θ)<∞. |
Corollary 1 implies that
0<Hq,s+tμ×ν(A×A)≤Pq,s+tμ×ν(A×A)<∞. |
Example 2. Let μ,ν∈M(R), q∈R, and let A and B be two sets of points in the x-axis and y-axis, respectively. In this example, we give a sufficient condition to obtain
bqμ×ν(A×B)=bqμ(A)+bqν(B). |
From Theorem 1, we have
bqμ×ν(A×B)≥bqμ(A)+bqν(B), |
so we only have to prove the inverse inequality. For this, for t,s∈R, we define the lower ζt-dimensional density of A at the point y as
Dζt(y)=lim infr→0infx∈BHq,tν(A∩B(y,r))ν(B(x,r))q(2r)t. |
Fix r>0 and define the set Iy(r) as the centered interval on y with the length r. For n≥1, consider the set
Bn={y∈B,Hζt(B∩Iy(r))>supx∈Bν(Ix(r))qrt/n,∀r≤n−1}. |
Assume that Dζt(y)>0 for all y∈F, which implies clearly that Bn↗B. In addition, if we prove that
Hq,s+tμ×ν(A×Bn)<+∞ | (3.4) |
for some n∈N, then we deduce that
bμ×ν(A×B)=s+t. |
This gives the result if we choose
t=bqν(B)ands=bqμ(A). |
Now, we will prove (3.4). Let
˜A⊆Aand˜Bn⊆Bn. |
Let n be an integer and 0<r≤1/n; we then define
I(r)={Iy(r), y∈˜Bn}. |
We can extract f a finite subset J(r) rom I(r) such that ˜Bn⊂J(r) and no three intervals of J(r) have points in it.
Lemma 4. For 0<r≤1/n, we have
J(r)≤2nr−t(supx∈Bν(Ix(r)))−qHζt(B). | (3.5) |
Proof. Divide the set J(r) into J1(r) and J2(r) such that in each of them the intervals do not overlap. Using the definition of the set Fn, we get
(supx∈Fν(Ix(r)))−qr−tnHζt(B)≥∑I∈J1(r)(supx∈Bν(Ix(r)))−qr−tnHζt(B∩I)>#J1(r). |
Similarly, we obtain
#J2(r)≤(supx∈Fν(Ix(r)))−qr−tnHζt(B) |
as required.
In the other hand, for ϵ>0, a sequence of sets {Ai} exists such that
˜A⊆⋃iAi |
and that
∑i¯Hξs0(Ai)≤Hξs(A)+ϵ. |
Thus, we have a sequence {Bi,j} of intervals of length r covering ˜A such that the family {Bi,j}j, for each i, is a covering of Ai and
∑iNqμ,r/2(Ai)rs≤Hξs(A)+2ϵ. | (3.6) |
Let [a,b] represent any interval within the set {Bi,j}. Enclose all points in this set that fall between the lines x=a and x=b with squares whose sides are parallel to these lines. The projections of these squares onto the y-axis correspond to intervals in J(r). In a similar manner, construct sets of squares for each interval in {Bi,j}, and denote the set of squares associated with the interval [a,b] as C(a,b). Since the number of squares in C(a,b) does not exceed the number of intervals in J(r), and each square intersecting ˜AטBn can be inscribed within a centered ball of diameter r′=3r, it follows that:
Nqμ×ν,r′/2(˜AטBn)≤#J(r)supx∈Fν(Ix(r))q∑i,jμ(Bi,j)q. |
Thus, using (3.5) and (3.6), we get
¯Hq,s+tμ×ν,r′/2(˜AטBn)≤2nr−tHξt(B)(3r)s+t∑i,jμ(Bi,j)q≤2×3s+tnHζt(B)∑iNqμ,r/2(Ai)rs≤2×3s+tnHζt(B)(Hξs(A)+2ϵ). |
Since ϵ is arbitrarily, we get
Hs+t0(˜AטBn)≤2×3s+tnHζt(B)Hξs(A). |
Finally, we have
¯Hs+t(A×Bn)≤2×3s+tnHζt(B)Hξs(A), |
from which the Eq (3.4) follows.
The result given in this example can be summarized in the next theorem.
Theorem 3. Let E and F be sets of points in x-axis and y-axis, respectively. Set
s=bqμ(A)andt=bqν(B) |
and assume that Hξs(A),Hζt(B)∈(0,∞), and, for all y∈F, Dζt(y)>0. In this case,
bqμ×ν(A×B)=bqμ(A)+bqν(B). |
We define the set G of all continuous and increasing functions h on [0,t0) for some t0>0 satisfying h(0)=0, and the function
t⟼h(t)/td |
is decreasing. We assume in this section that h∈G and that it t satisfies the doubling condition
h(2t)≤2dh(t),for0<t<t0/2. |
A cube I(x,r) in Rd is a subset of the form
I(x,r)=n∏i=1[xi−r,xi+r]. |
For a cube I, we use l(I) to denote its side length. In this section, using cubes with sides of a length less than δ rather than closed balls, we define a generalized Hausdorff measure ˜Hq,hμ equivalent to the generalized Hausdorff measure Hq,hμ. We prove that this measure is appropriate for estimating the measure of the generalized Cantor set. Let μ∈PD(Rd), h∈F0, and q∈R. Define
˜Hq,hμ,0(A)=limδ→0˜Hq,hμ,δ(A), |
where
˜Hq,hμ,δ(A)=inf∑iμ(B(xi,ri))qh(|Ii|) |
with the infimum being taken over all coverings of A by cubes with sides of a length ≤δ. Then a constant C exists such that
C−1˜Hq,hμ,0(A)≤Hq,hμ,0(A)≤C˜Hq,hμ,0(A). |
We will compute the estimation of the generalized Hausdorff measure of the Kd. More precisely, we have the following result.
Theorem 4. Let Kd be the d-dimensional symmetric generalized Cantor set (d≥1) constructed by the system {L,{nk}k≥1,{λk}k≥1}. We then have
2−3dlim infk→∞(n1n2…nk)dλqkh(λk)≤Hq,hμ,0(Kd)≤Pq,hμ,0(Kd)≤Mlim supk→∞(n1n2…nk)dλqkh(λk). |
Proof. We focus on proving only the left-hand inequality; the validity of the right-hand inequality can be established using similar argument. Let Ψ be the set function in Lemma 1. Let ε be a positive number with ε≤r0 and {Ii} be a ε-covering of Kd by open cubes with the sides ri≤ε. We have
∑iμ(Ii)qh(ri)≥2−3d∑iΨ(Ii)≥2−3dΨ(⋃iIi)≥2−3db. |
Since b is an arbitrary number such that
b<lim infk→∞(n1n2…nk)dλqkh(λk), |
then we get the desired result.
In this example, we take d=1 and we consider the one-dimensional generalized Cantor set K1 (resp. K2) constructed by the system {L,{nk}k≥1,{λk}k≥1} (resp. {L,{nk}k≥1,{Λk}k≥1}) In the following, we consider l=1,d=1,nk=2, and
λk=kξ12−k/αΛk=k−ξ22−k/βh(t)=tαg(t)=tβ |
Theorem 5. The constants M and M′ exist such that
Mlim infk→∞2kλq+αk2kΛq+βk≤¯Hq,hgμ×ν,0(K1×K2)≤¯Pq,hgμ×ν(K1×K2)≤M′lim supk→∞2kλq+αk2kΛq+βk. |
Proof. We focus on proving only the left-hand inequality; the validity of the right-hand inequality can be deduced using the same idea. Assume that
A:=lim infk→∞2kλq+αk2kΛq+βk>0; |
otherwise, the result remains trivial. Let
0<B<A |
and choose a positive integer k1 satisfying the following inequality:
B<2kλq+αk2kΛq+βk |
for all k≥k1. Now we define the sequence (˜Λk)k≥k1 as
B=2kλq+αk2k˜Λq+βk. |
It follows that
˜Λk<Λkand22λq+αk+1˜Λq+βk+1=λq+αk˜Λq+βk | (4.1) |
for all k≥k1.
Let
K⊂K1×K2 |
and use Ik1 (resp. Ik2) to denote any of the closed intervals of the generation r of K1 (resp. K2). Then
Nqμ×ν,k+1(K)=inf{∑iμ×ν(Ir+11×Ik+12)q,Ik+11×Ik+12 meetingK}≤inf{∑iμ(Ir+11)qν(Ik+12)q,Ik+11×Ik+12 meetingK}. |
Note that
λk+1=λk(k+1k)ξ12−1/αandΛr+1=Λk(kk+1)ξ22−1/β, |
and then
Nqμ×ν,k+1(K)≤inf{∑iμ(Ik+11)qν(Ik+12)q,Ik+11×Ik+12 meetingK}≤kk+12−q/α2−q/β(k+1k)qξ1−qξ2inf{∑iμ(Ik1)qν(Ik2)q,Ik1×Ik2 meetingK}=222−q/α2−q/β(k+1k)qξ1−qξ2Nqμ×ν,k(K),Nqμ×ν,k+1(K)λαk+1˜Λβk+1≤222−q/α2−q/β(k+1k)qξ1−qξ2λαk+1˜Λβk+1Nqμ×ν,k(K)≤222−q/α2−q/βλqk+1˜Λqr+1(k+1k)qξ1−qξ2λq+αk+1˜Λq+βk+1Nqμ×ν,k(K)≤(4.1)2−q/α2−q/βλqk+1˜Λqk+1(k+1k)qξ1−qξ2λq+αk˜Λq+βkNqμ×ν,k(K)≤(4.1)[2−1/α2−1/βλk˜Λkλk+1˜Λk+1(k+1k)ξ1−ξ2]qλαk˜ΛβkNqμ×ν,k(K). |
It follows that the sequence {Nqμ×ν,k(K)λαk˜Λβr} is decreasing, and we may define the function
Φ(A)=limk→0Nqμ×ν,k(A)λαk˜Λβk. |
Case β≤α. We can choose k2>k1 such that
Λk<λk+1for all k≥k2. |
Let
so=Λk2 |
and consider any two-dimensional open cube I with the side s≤s0. Let p and k be the unique positive integers such that
λp+1<s≤λpandΛk+1<s≤Λk. |
Since
λp+1<Λk<λk+1 |
for k≥k2, we deduce that k<p. Moreover, the open cube I meets at most 22 rectangles of the form Ip1×Ik2 and so meets at most 24 rectangles of the form Ip+11×Ik+12. Therefore, since p>k, it follows that
Nqμ×ν,p+1(I)≤inf{∑iμ(Ip+11)qν(Ip+12)q,Ip+11×Ip+12 meeting I}≤242p−rλqp+1Λqp+1. |
Since 2kΛβk decrease as r increases, note that
2p−kΛβp+1<Λβk+1. |
Then,
Φ(I)≤Nqμ×ν,p+1(I)λαp+1˜Λβp+1≤24+p−kλqp+1Λqp+1λαp+1˜Λβp+1≤24+p−kμ(Qp+1)qν(Q(p+1))qλα(p+1)Λβp+1≤24μ(Q(p+1))qν(Q(p+1))qsα+β. |
Example 3. As a consequence, we construct an estimate of the generalized packing measures of product sets of one-dimensional generalized Cantor sets. Let 0<α and β<1. In this example, we consider the one-dimensional generalized Cantor set K1 (resp. K2) constructed by the system {l,{kr}r≥1,{λr}r≥1} (resp.{l,{kr}r≥1,{Πr}r≥1}). Set l=1 and nk=2 and consider in the following:
λk=(k22−k)1α+q,Λk=(k−j2−k)1β+q,h(t)=tα,andg(t)=tβ. |
(1) We have
limk→∞2kλq+αk2kΛq+βk=limk→∞2kλq+αk2kΛq+βk=limk→∞(k22−k)(k−j2−k)2k=limk→∞k2−j. |
Therefore, ¯Hq,hgμ×ν,0(K1×K2) (resp. ¯Pq,hgμ×ν(K1×K2)) is infinite, positive finite, and zero for j=1,2,3, respectively.
(2) We have
limk→∞2kλq+αk=limk→∞2k(k22−k)=∞. |
Therefore,
¯Hq,hμ,0(K1)=¯Pq,hμ(K1)=∞. |
(3) We have
limk→∞2kΛq+αk=limk→∞2k(k−j2−k)=0. |
Therefore,
¯Hq,gν,0(K2)=¯Pq,gν(K2)=0. |
Let A⊆Rd and B⊆Rl. In this work, we present a novel approach that is distinct from that in [30], as it is specifically tailored for Euclidean spaces, to establish the following inequality:
Hq,hμ(A)Hq,gν(B)≤c1Hq,hgμ×ν(A×B)≤c2Hq,hμ(A)Pq,gν(B)≤c3Pq,hgμ×ν(A×B)≤c4Pq,hμ(A)Pq,gν(B). |
This result holds under the assumption that μ,ν,h,g satisfy the doubling condition and that none of the products is of the form 0×∞ or ∞×0. Furthermore, by analyzing the measures of symmetric generalized Cantor sets, we demonstrate that the exclusion of the 0–∞ condition is indispensable and thus cannot be omitted. Let (X,ρ) and (X′,ρ′) be two separable metric spaces. The result presented in this paper holds true for both X and X′, though the approach used in our proof does not extend to metric spaces.
(1) Let B(X) denote the family of closed balls in X, and let Φ(X) represent the class of pre-measures. A pre-measure is any increasing function
ξ:B(X)→[0,+∞] |
satisfying
ξ(∅)=0. |
It is natural to consider a general construction of Hq,ξμ, defined using a measure μ and a pre-measure ξ. Specifically, our result applies when
ξ(B(x,r))=h(2r) |
and allows for the choice
ξ(B)=h(|B|) |
for all B∈B(X). Let
ξ∈Φ(X)andξ′∈Φ(X′). |
We define ξ0, the Cartesian product measure generated from the functions ξ and ξ′, on B(X×X′) as
ξ0(B×B′)=ξ(B)ξ′(B′), for all B∈B(X),B′∈B(X′). |
We strongly believe that the resulting measure is particularly well-suited for studying Cartesian product sets. Under a suitable doubling condition, we obtain the following result:
Hq,ξ0μ×ν(A×B)=Hq,ξμ(A)Hq,ξ′ν(B), | (5.1) |
for all A⊂X and B⊂X′. This construction was first introduced by Kelly in [50]; see also [51].
(2) To establish the equality presented in Eq (5.1), we draw inspiration from the work of Kelly [50]. Specifically, we propose constructing a weighted lower H-W measure, denoted Wq,hμ, for any given Hausdorff measure h. This approach involves assigning non-negative weights to the covering sets, adhering to what is commonly referred to as the third method for constructing an outer measure. On the basis of this framework, we conjecture that the equality in (5.1) holds if the constructed weighted measure satisfies
Wq,ξμ=Hq,ξμ. |
Similarly, one can construct a weighted upper H-W measure, denoted Qq,hμ, by following the same approach used for the weighted lower H-W measure but replacing covering with packing [8]. We conjecture that the equality
Pq,ξ0μ×ν(A×B)=Pq,ξμ(A)Pq,ξ′ν(B), |
for all A⊂X and B⊂X′, holds if the constructed weighted measure satisfies
Qq,ξμ=Pq,ξμ. |
(3) A similar result to (1.2) and (1.3) can be achieved by examining fractal pseudo-packings and weighted measures of the H-S type. The purpose of employing these generalizations is to eliminate the need for assuming the doubling condition.
(4) Our results in this paper can be readily extended to the setting of generalized lower and upper H-S measures, denoted Hq,hμ1×μ2 and Pq,hμ1×μ2. These fractal measures play a crucial role in the multifractal analysis of a measure relative to another measure [52].
The author declares he has not used Artificial Intelligence (AI) tools in the creation of this article.
This work was supported by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia [KFU251033].
The author declares no conflict of interest.
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