scholarly journals Some new Volterra-Fredholm type discrete inequalities with four iterated infinite sums with applications

2017 ◽  
pp. 495-510
Author(s):  
Sabir Hussain ◽  
Shaista Amat ur Rehman ◽  
Humaira Khalid ◽  
Qing-Hua Ma
2017 ◽  
pp. 495-510 ◽  
Author(s):  
Sabir Hussain ◽  
Shaista Amat ur Rehman ◽  
Humaira Khalid ◽  
Qing-Hua Ma

2011 ◽  
Vol 2011 ◽  
pp. 1-24 ◽  
Author(s):  
Bin Zheng ◽  
Qinghua Feng

Some new Volterra-Fredholm-type discrete inequalities in two independent variables are established, which provide a handy tool in the study of qualitative and quantitative properties of solutions of certain difference equations. The established results extend some known results in the literature.


2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Run Xu

Some generalized discrete Volterra-Fredholm-type inequalities were developed, which can be used as effective tools in the qualitative analysis of the solution to difference equations.


1996 ◽  
Vol 16 (5) ◽  
pp. 1087-1100
Author(s):  
Eric Slud ◽  
Daniel Chambers

abstractNecessary and sufficient analytical conditions are given for homogeneous multiple Wiener-Itô integral processes (MWIs) to be mixing, and sufficient conditions are given for mixing of general square-integrable Gaussian-subordinated processes. It is shown that every finite or infinite sum Y of MWIs (i.e. every real square-integrable stationary polynomial form in the variables of an underlying weakly mixing Gaussian process) is mixing if the process defined separately by each homogeneous-order term is mixing, and that this condition is necessary for a large class of Gaussian-subordinated processes. Moreover, for homogeneous MWIs Y1, for sums of MWIs of order ≤ 3, and for a large class of square-integrable infinite sums Y1, of MWIs, mixing holds if and only if Y2 has correlation-function decaying to zero for large lags. Several examples of the criteria for mixing are given, including a second-order homogeneous MWI, i.e. a degree two polynomial form, orthogonal to all linear forms, which has auto-correlations tending to zero for large lags but is not mixing.


Author(s):  
Mohammed Charif Bounaya ◽  
Samir Lemita ◽  
Mourad Ghiat ◽  
Mohamed Zine Aissaoui

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