2019
DOI: 10.1186/s13660-019-2039-1
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A Hilbert-type integral inequality under configuring free power and its applications

Abstract: By using the method of weight function, the technique of real analysis, and the theory of special functions, a multi-parameter Hilbert-type integral inequality and its equivalent form are established, and their constant factors are proved to be the best possible. The expressions of operator with norm are given. As an application, relevant results in the references and some new inequalities are obtained by assigning some parameter values.

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Cited by 13 publications
(7 citation statements)
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“…In 2017, Hong [18] proved an equivalent condition between (3) and a few parameters. Some similar results were obtained in [19][20][21][22][23][24][25][26][27][28].…”
Section: Introductionsupporting
confidence: 82%
“…In 2017, Hong [18] proved an equivalent condition between (3) and a few parameters. Some similar results were obtained in [19][20][21][22][23][24][25][26][27][28].…”
Section: Introductionsupporting
confidence: 82%
“…The research of Hilbert-type integral inequalities with hybrid kernels is one of the important contents too. The so-called hybrid kernel research is to combine some basic kernels into new integral kernels and do the corresponding research works, which began in 2008 and yielded a lot of results (see previous studies [21][22][23][24][25]. In this paper, by introducing the parameters 1 , 2 , 3 , 4 , the basic kernels k 1 (x, ) = 1 x+ , k 2 (x, ) =…”
Section: Liumentioning
confidence: 99%
“…The research of Hilbert‐type integral inequalities with hybrid kernels is one of the important contents too. The so‐called hybrid kernel research is to combine some basic kernels into new integral kernels and do the corresponding research works, which began in 2008 and yielded a lot of results (see previous studies 21‐25 ). In this paper, by introducing the parameters λ 1 , λ 2 , λ 3 , λ 4 , the basic kernels k1false(x,yfalse)=1x+y,k2false(x,yfalse)=||lnyxx+y,k3false(x,yfalse)=maxfalse{x,yfalse},k4false(x,yfalse)=minfalse{x,yfalse} are parametric combined to a mixed kernel as kfalse(x,yfalse):=||lnyxλ1false(minfalse{x,yfalse}false)λ2false(x+yfalse)λ3false(maxfalse{x,yfalse}false)λ4.…”
Section: Introductionmentioning
confidence: 99%
“…In 2013, Yang [25] also studied the equivalence of ( 6) and (7) by adding a condition h(u) = k λ (u, 1). In 2017, Hong [9] studied an equivalent condition for (6) involving certain parameters, and some further related results were established in [4], [5], [15], [29], [28].…”
Section: Introductionmentioning
confidence: 99%