Abstract
By using two-parameter functions, this paper presents a family of new Wilker and Huygens type inequalities involving inverse trigonometric functions. It can recover parts of previous results, and can also achieve much better approximation performance than those of prevailing methods. The application of approximating the integral computation is shown by numerical examples, which shows the better approximation effect of the new method. More other forms of bounding functions, or even three-parameter functions, can be used for further improvement.
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1 Introduction
The inequalities involving circular and hyperbolic functions has caused wide interests of many researchers, see also [1, 2, 5,6,7,8,9,10,11, 13,14,15,16,17,18,19,20,21,22,23,24, 26,27,34, 36,37,43, 45,46,50] and the references therein. In particular, the following inequalities involving trigonometric functions
and
have been obtained by Wilker [32] and Huygen [12], and are referred as Wilker and Huygens type inequalities. The following inequalities
and
are the counterparts of Eqs. (1) and (2) for the hyperbolic functions, where the proofs are referred to [44] and [25], respectively. Wilker and Huygens type inequalities have also been established for the lemniscate functions and Jacobian elliptic and theta functions [26, 31], for circular functions [49, 50], for hyperbolic functions [6], and so on. The Wilker and Huygens type inequalities involving inverse trigonometric functions
have also been discussed in many references [2,3,4,5,6, 15, 18, 19, 22, 25, 26, 31, 35, 49, 50].
For \(x \in (0,1)\), the following inequalities
and
are obtained in [3] and [19], where \(\dfrac{17}{45}\) and \(\dfrac{\pi ^2+\pi -8}{\pi }\), \(\dfrac{5\pi -12}{\pi }\) and \(\dfrac{7}{20}\) are the best constants in Eqs. (6) and (7), respectively.
This paper provides much sharper bounds by using the following two-parameter functions
where \(A_{i,n}(x)\) and \(B_{i,n}(x)\) are polynomials of degree n satisfying either Eqs. (9) or (10)
where \( { D_i(x)=f_i(x)- G_{i,n}(x,\alpha ), ~~D_{i+2}(x)=f_i(x)- H_{i,n}(x,\alpha ), ~~i=1,2 }\).
This paper takes the \(n=3\) case as an example, the cases of \(n>3\) can also be done in a similar way. Firstly, one obtains that
Secondly, by using the Maple software, it can be verified that
By solving \(F_1^{(6)}(0)=0\), \(F_2^{(4)}(0)=0\), \(F_3^{(6)}(0)\) and \(F_4^{(4)}(0)=0\), one obtains the values of \(\alpha \) in \(G_{i,3}(x,\alpha )\). The main results are as follows.
Theorem 1
For \(x \in (0,1)\), one obtains the following inequalities
Theorem 2
For \(x \in (0,1)\), one obtains the following inequalities
Theorem 3
For \(x \in (0,1)\), one obtains the following inequalities
Theorem 4
For \(x \in (0,1)\), one obtains the following inequalities
As shown in Fig. 1, the bounds of \(f_i(x)\) from Eqs. (12–14) achieve much better approximation effect than those of Eqs. (6) and (7), see also Eqs. (31) and (32) and the corresponding proofs in Sect. 3.
2 Proofs of Theorems 1–4
Firstly, we have the following lemmas.
Lemma 1
The following inequalities
hold for all \(x \in (0,1)\), where
Proof
Let \(H_i(x)=\arctan (x)-l_i(x)\), \(i=1,2,3,4\). Let
It can be verified that
such that \(x_i\) is the unique root of \(H_i^{'}(x)\) within (0, 1), \(i=1,2,3,4\), and
Combining Eq. (17) with Eq. (18), \(\forall x \in (0,1)\), one has that
where leads to Eq. (16), and the proof is completed.
Lemma 2
The following inequalities
hold for all \( x \in (0,1)\), where
Proof
Let \(E_i(x)=\arcsin (x)-l_{i+4}(x)\), \(i=1,2,\ldots ,5\). For \(x \in (0,1)\), it can be verified that
From Eq. (20), for \(x \in (0,1)\), there exists \(\phi _i(x) \in (0,1)\), \(i=1,2,\ldots ,5\), such that
On the other hand, we have that
Combining Eq. (21) with Eq. (22), we obtain Eq. (19), and the proof is completed.
2.1 Proof of Theorem 1
Combining with Lemmas 1 and 2, for \(\forall x \in (0,1)\), by using the Maple software, let
it can be verified that
and
Combining Eq. (23) with Eq. (24), one obtains Eq. (12), and the proof of Theorem 1 is completed.
2.2 Proof of Theorem 2
Combining with Lemmas 1 and 2, for \(\forall x \in (0,1)\), by using the Maple software, let
it can be verified that
and
Combining Eq. (25) with Eq. (26), one obtains Eq. (13) and completes the proof of Theorem 2.
2.3 Proof of Theorem 3
Combining with Lemma 1 and Lemma 2, for \(x \in (0,1)\), by using the Maple software, let
it can be verified that
and
Combining Eq. (27) with Eq. (28), Theorem 3 has been proved.
2.4 Proof of Theorem 4
Combining with Lemma 1 and Lemma 2, by using the Maple software, let
for \(x \in (0,1)\), it can be verified that
and
Combining Eq. (29) with Eq. (30), Theorem 4 has been proved.
3 More discussions
Firstly, the new method can recover previous results in Eqs. (6) and (7) in [3, 19]. It can be verified that \(\bar{G}_{1,3}(x,1)=L_1(x)\) and \(\bar{G}_{2,3}(x,1)=R_1(x)\), \(\bar{G}_{3,3}(x,1)=L_2(x)\) and \(\bar{G}_{4,3}(x,1)=R_2(x)\), so both Eqs. (6) and (7) are recovered.
Secondly, the new method can achieve much better approximation performance. Let \(D_3(x)=\dfrac{R_1(x)-\bar{G}_{2,3}(x,0)}{x^3}\) and \(D_4(x)=L_1(x)-\bar{G}_{1,3}(x,\sqrt{\dfrac{27}{119}})\). We have that \(D_4^{'}(x)=\dfrac{-1564 x^2}{45 (x^2+1) (119+27 x^2)}\) and \(D_3^{'}(x)=\dfrac{- (\pi ^2+\pi -8) (\pi x^2+\pi -4)}{4 \pi (x^2+1)}\) has a unique simple root \(x_4 = \sqrt{\dfrac{4-\pi }{\pi }}\) within (0, 1), such that
which leads to
Let \(D_5(x)=\dfrac{R_2(x)-\bar{G}_{4,3}(x,0)}{x^3}\) and \(D_6(x)=L_2(x)- \bar{G}_{3,3}(x,\dfrac{3 \sqrt{10}}{14})\). We have that \(D_6^{'}(x)=\dfrac{-371 x^2}{20 (x^2+1) (98+45 x^2)}\) and \(D_5^{'}(x)=\dfrac{- (5\pi -12)(\pi x^2+\pi -4)}{4 \pi (x^2+1)}\) has a unique simple root \(x_5 = \sqrt{\dfrac{4-\pi }{\pi }}\) within (0, 1), such that
which leads to
From Eqs. (31) and (32), both Eqs. (12) and (13) achieve better approximation effect than those of Eqs. (6) and (7), see also the error plots shown in Fig. 1.
Finally, we have tested the errors for approximating the integral of \(f_i(x)\) by using the bounds in Eqs. (6, 7) and (12–14). Table 1 shows that the approximation errors from (12–14) are much better than those of Eqs. (6, 7).
As for future work, there is still great scope for further development. In principle, more forms of the two-parameter functions, or even three-parameter functions, can be used for sharpening the bounds of Wilker and Huygens type inequalities. On the other hand, the idea can be extended for more other types of inequalities.
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Acknowledgements
This research work was partially supported by Zhejiang Key Research and Development Project of China (LY19F020041, 2018C01030), the National Natural Science Foundation of China (61972120, 61672009).
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Chen, XD., Wang, H., Yang, K. et al. New bounds of Wilker- and Huygens-type inequalities for inverse trigonometric functions. RACSAM 115, 36 (2021). https://doi.org/10.1007/s13398-020-00969-2
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DOI: https://doi.org/10.1007/s13398-020-00969-2
Keywords
- Wilker and Huygens type inequality
- Tighter bounds
- Integral approximation error
- Inverse trigonometric function
- Two-parameter function