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Sub-stabilizability and super-stabilizability for bivariate means
© Raïssouli and Sándor; licensee Springer. 2014
- Received: 27 July 2013
- Accepted: 18 December 2013
- Published: 24 January 2014
The stability and stabilizability concepts for means in two variables have been introduced in (Raïssouli in Appl. Math. E-Notes 11:159-174, 2011). It has been proved that the arithmetic, geometric, and harmonic means are stable, while the logarithmic and identric means are stabilizable. In the present paper, we introduce new concepts, the so-called sub-stabilizability and super-stabilizability, and we apply them to some standard means.
- stable means
- stabilizable means
- sub-stabilizable means
- super-stabilizable means
and are known as the arithmetic, geometric, harmonic, logarithmic, and identric means, respectively.
A mean m is symmetric if for all , and monotone if is increasing in a and in b, that is, if (resp. ) then (resp. ). For more details as regards monotone means, see .
For a given mean m, we set , and it is easy to see that is also a mean, called the dual mean of m. Every mean m satisfies , and if and are two means such that then . Further, the arithmetic and harmonic means are mutually dual (i.e. , ) and the geometric mean is self-dual (i.e. ).
Let p be a real number. The next means are of interest.
The power (binomial) mean:
The power logarithmic mean:
We end this section by recalling the next result which will be needed in the sequel.
Further these inequalities are the best possible i.e. , , are the best power logarithmic means lower bounds of P, M, T, while , , are the best power (binomial) means upper bounds of P, M, T, respectively. Otherwise, there is no such that P, M or T is strictly less that .
For the sake of simplicity for the reader, we recall here more basic notions and results that will be needed in the sequel, see  for more details. We begin by the next definition.
called the resultant mean-map of , , and .
We also recall the next result, see .
Stable if .
Stabilizable if there exist two nontrivial stable means and satisfying the relation . We then say that m is -stabilizable.
A developed study about the stability and stabilizability of the standard means was presented in . In particular the next result has been proved there.
The power binomial mean is stable for all real number p. In particular, the arithmetic, geometric, and harmonic means A, G, and H are stable.
The power logarithmic mean is -stabilizable for all real number p.
The logarithmic mean L is -stabilizable and -stabilizable while the identric mean I is -stabilizable.
Remark 2.1 The symmetry character of the above involved mean is, by definition, taken as essential hypothesis. In fact, if we attempt to extend the above concepts to non-symmetric means by keeping the same definitions (Definition 2.1 and Definition 2.2), the simple means , with , , do not satisfy . In another way, the definition of ℛ, together with that related to the stability and stabilizability concepts, is not exactly the same as above, but must be investigated for non-symmetric means. We leave the details as regards the latter point to a later time.
The next definition is also needed here .
A symmetric mean m will be called cross mean if the map is symmetric in its four variables.
It is proved in  that every cross mean is stable. The reverse of the latter assertion is still an open problem. Otherwise, it is conjectured  that the first Seiffert mean P is not stabilizable and such a problem is also still open. We also conjecture here that the second Seiffert mean and the Neuman-Sándor mean are not stabilizable either.
The next result needed here has also been proved in .
Theorem 2.3 Let and be two nontrivial stable symmetric monotone means such that (resp. ). Assume that is moreover a cross mean. Then there exists one and only one -stabilizable mean m such that (resp. ).
is obvious. By virtue of this equivalence, it will be sufficient to study the properties of one the sets and and to deduce that of the other by duality.
Example 3.1 With the help of Theorem 2.1, it is simple to see that and . So and . We can also verify that and . Other more interesting examples will be seen later.
The next result is of interest.
Proposition 3.1 Let , be two nontrivial monotone (symmetric) stable means where is a cross mean. Then the intersection between and is reduced to the unique mean m which is the -stabilizable mean.
Proof Following Theorem 2.3, let m be the unique -stabilizable mean. Then and so and . Inversely, let ; then and so m is the unique -stabilizable mean. □
Now, we are in a position to state the next result ensuring the existence of a maximal super-stabilizable (resp. minimal sub-stabilizable) mean.
Theorem 3.2 Let , be two symmetric monotone means. Then the set has at least a maximal element.
Before giving the proof of the last theorem we state the next corollary, which is immediate from the above.
Corollary 3.3 Let , be as in the above theorem. Then the set has at least a minimal element.
Since and are monotone, we deduce by Theorem 2.1, for all and so , that is, . It follows that every nonempty totally ordered subset of has an upper bound in , that is, is inductive. We can then apply the classical Zorn lemma to conclude and the proof of the theorem is complete. □
The sets and are (linearly) convex.
The sets and are geometrically convex.
Proof (1) follows from the linear-affine character of A with the definition of ℛ, while (2) comes from the geometric character of G. The details are simple and omitted here. □
The next definition may be stated.
-sub-stabilizable if and m is between and ,
-super-stabilizable if and m is between and .
Following Theorem 2.3, the above definition extends that of stabilizability in the sense that a mean m is -stabilizable if and only if (a) and (b) hold. It follows that the above concepts bring something new for non-stable and non-stabilizable means. For this, we say that m is strictly -sub-stabilizable if and m is strictly -super-stabilizable if , with in both cases m being strictly between and .
Example 4.1 We can easily see that G is -super-stabilizable (but not strictly) while A is -sub-stabilizable. However, T and M are not -sub-stabilizable, since they are not between G and A. More interesting examples, presented as main results, will be stated in the section below.
If there exists a symmetric mean such that m is -sub-stabilizable then .
If there exists a symmetric mean such that m is -super-stabilizable then .
It is similar to that the above. The details are omitted here. □
The above theorem has various consequences, which we will state in what follows.
If m is -sub-stabilizable for some then . In particular, if m is -sub-stabilizable then .
If m is -super-stabilizable for some then . In particular, if m is -super-stabilizable then .
Proof It is immediate by combining the above theorem with the fact that for each real number p, and , . □
The above corollary implies that I is not -super-stabilizable, but it is perhaps -sub-stabilizable. See more details as regards the latter point in the section below.
Corollary 4.3 Let be a strictly -sub-stabilizable mean. Then , where q is the greatest number such that and r is the smallest number such that .
Proof If is strictly -sub-stabilizable then, by definition, and, by the above corollary, . Combining these latter mean-inequalities we deduce the desired result. □
If M is strictly -sub-stabilizable for some p then .
If T is strictly -sub-stabilizable then .
There is no such that P, M or T is -super-stabilizable.
Proof Combining the above corollary with Theorem 1.1, we immediately deduce the assertions (i), (ii), and (iii).
Assertion (iv) follows from Corollary 4.2(ii) with Theorem 1.1 again. Details are omitted here. □
This section will be devoted to an application of the above concepts to some known means. We begin with the next result.
Theorem 5.1 The logarithmic mean L is strictly -super-stabilizable.
for all with . We will present two different proofs for equation (5.1). By the symmetric character of the involved means, we can assume, without loss the generality, that .
The first method is much more natural: Since , we have
This gives equation (5.1), so it completes the proof of the first method.
The second method is based on the fact that we can always set and with . A simple computation leads to
for all , which clearly holds and inequality (5.1) is again proved.
In summary, we have shown that L is strictly -super-stabilizable. □
which, with , means that L is strictly -sub-stabilizable.
Theorem 5.2 The identric mean I is strictly -sub-stabilizable.
Proof We will present here two different methods for proving our claim: The first is direct and based on some mean-inequalities already stated in the literature, while the second one is similar to above.
First method: We have to show(5.2)
It follows that Φ is strictly decreasing for and so . The second method is complete. □
Remark 5.2 Another method for proving equation (5.4) can be stated as follows: It is well known (and easy to verify) that for all , where is the so-called weighted geometric mean. With this, equation (5.4) is equivalent to i.e. , which is a well-known mean-inequality.
As a consequence of the above, the next result gives a double inequality refining and involving the four standard means G, L, I, and A.
This, with Example 2.1 and a simple manipulation, gives the desired result. □
Of course, the above theorems when combined with the properties of sub-super-stabilizability imply that is, simultaneously, strictly -sub-stabilizable and strictly -super-stabilizable, while is strictly -super-stabilizable.
As already pointed out before, whether the first Seiffert mean P is stabilizable still is an open problem. However, the next result may be stated.
Theorem 5.4 The first Seiffert mean P is strictly -sub-stabilizable.
holds for all with . We also present here two different methods.
First method: this method is analogous to the above. Simple computation leads to
for all . The desired inequality follows in the same way as previously.
Second method: this method is based on an integral form of . It is easy to see that, for all (with without loss the generality), we have(5.7)
from which equation (5.10) follows. The proof is complete. □
which is exactly equation (5.6).
for all . We then present the following.
Problem 1: Prove or disprove that the first Seiffert mean P is strictly -super-stabilizable.
Problem 2: Find the best real numbers and for which P is strictly -sub-stabilizable.
Problem 3: Are the means T and M strictly -sub-stabilizable for some real numbers , ?
The present work was supported by the Deanship of Scientific Research of Taibah University.
- Bullen PS Mathematics and Its Applications. In Handbook of Means and Their Inequalities. 2nd edition. Springer, Berlin; 1987.Google Scholar
- Seiffert HJ: Problem 887. Nieuw Arch. Wiskd. 1993, 11: 176.MathSciNetGoogle Scholar
- Seiffert HJ: Aufgabe 16. Wurzel 1995, 29: 87.Google Scholar
- Neuman E, Sándor J: On the Schwab-Borchardt mean. Math. Pannon. 2003,14(2):253-266.MathSciNetMATHGoogle Scholar
- Raïssouli M, Sándor J: On a method of construction of new means with applications. J. Inequal. Appl. 2013., 2013: Article ID 89Google Scholar
- Chu YM, Long BY, Gong WM, Song YQ: Sharps bounds for Seiffert and Neuman-Sándor means in terms of generalized logarithmic means. J. Inequal. Appl. 2013., 2013: Article ID 10Google Scholar
- Chu YM, Long BY: Bounds of the Neuman-Sándor mean using power and identric means. Abstr. Appl. Anal. 2013., 2013: Article ID 832591Google Scholar
- Hästö, PA: Optimal inequalities between Seiffert’s mean and power means. MIA Preprint (2013)Google Scholar
- Yang, ZH: Sharp bounds of the second Seiffert mean in terms of power means (2012). arXiv: 1206.5494v1
- Yang, ZH: Sharp power means bounds for Neuman-Sándor mean (2012). arXiv: 1208.0895
- Raïssouli M: Stability and stabilizability for means. Appl. Math. E-Notes 2011, 11: 159-174.MathSciNetMATHGoogle Scholar
- Raïssouli M: Stabilizability of the Stolarsky mean and its approximation in terms of the power binomial mean. Int. J. Math. Anal. 2012,6(18):871-881.MathSciNetMATHGoogle Scholar
- Raïssouli M: Refinements for mean-inequalities via the stabilizability concept. J. Inequal. Appl. 2012., 2012: Article ID 55Google Scholar
- Raïssouli M: Positive answer for a conjecture about stabilizable means. J. Inequal. Appl. 2013., 2013: Article ID 467Google Scholar
- Sándor J: Monotonicity and convexity properties of means. Octogon Math. Mag. 1999,7(2):22-27.MathSciNetGoogle Scholar
- Sándor J: On certain inequalities for means, III. Arch. Math. 2001, 76: 34-40. 10.1007/s000130050539View ArticleMathSciNetMATHGoogle Scholar
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