The main purpose of this paper is to establish the HSrmander-Mihlin type theorem for Fourier multipliers with optimal smoothness on k-parameter Hardy Spaces for k≥ 3 using the multi- parameter Littlewood-Paley theory...The main purpose of this paper is to establish the HSrmander-Mihlin type theorem for Fourier multipliers with optimal smoothness on k-parameter Hardy Spaces for k≥ 3 using the multi- parameter Littlewood-Paley theory. For the sake of convenience and simplicity, we only consider the case k 3, and the method works for all the cases k ≥ 3： Tmf（x1,x2,x3） =1/（（2π）＋n1＋n2＋n3） ∫ R n1×R n2×R n3 m（ξ）f（ξ）e 2π ix.ξ dξ. where x = （x1,x2,x3） ∈ Rn1 × Rn2 × R n3 and ξ = （ξ1,ξ2,ξ3） ∈ R n1 × Rn2 ×R n3. One of our main results is the following： Assume that m（ξ） is a function on Rn1＋n2＋n3 satisfying sup j,k,l ∈Z ｜｜mj,k,l｜｜ W（s1,s2,s3）〈∞ with si 〉 ni（1/p-1/2） for 1 ≤ i ≤ 3. Then Tm is bounded from HP（R n1 × R n2 ×R n3） to HP（R n1 ×R n2 × R n3） for all 0 〈 p ≤ 1 and ｜｜Tm｜｜ Hp→Hp≤ sup j,k,l∈Z ｜｜mj,k,l｜｜ W（s1,s2,s3） Moreover, the smoothness assumption on sl for 1 ≤ i ≤ 3 is optimal. Here we have used the notations mj,k,l （ξ）= m（2 j ξ1,2 k ξ2, 2 l ξ3） ψ（ξ1） ψ（ξ2） ψ（ξ3） and ψ（ξi） is a suitable cut-off function on R ni for 1 ≤ i ≤ 3, and W（s1,s2,s3） is a three-parameter Sobolev space on R n × R n2 × Rn 3. Because the Fefferman criterion breaks down in three parameters or more, we consider the Lp boundedness of the Littlewood-Paley square function of T mf to establish its boundedness on the multi-parameter Hardy spaces.展开更多
The purpose of this paper is to complement the results by Lanzani and Stein(2017) by showing the dense definability of the Cauchy-Leray transform for the domains that give the counter-examples of Lanzani and Stein(201...The purpose of this paper is to complement the results by Lanzani and Stein(2017) by showing the dense definability of the Cauchy-Leray transform for the domains that give the counter-examples of Lanzani and Stein(2017), where L^p-boundedness is shown to fail when either the "near" C^2 boundary regularity, or the strong C-linear convexity assumption is dropped.展开更多
We consider the problem of minimizing the average of a large number of smooth component functions over one smooth inequality constraint.We propose and analyze a stochastic Moving Balls Approximation(SMBA)method.Like s...We consider the problem of minimizing the average of a large number of smooth component functions over one smooth inequality constraint.We propose and analyze a stochastic Moving Balls Approximation(SMBA)method.Like stochastic gradient(SG)met hods,the SMBA method's iteration cost is independent of the number of component functions and by exploiting the smoothness of the constraint function,our method can be easily implemented.Theoretical and computational properties of SMBA are studied,and convergence results are established.Numerical experiments indicate that our algorithm dramatically outperforms the existing Moving Balls Approximation algorithm(MBA)for the structure of our problem.展开更多
文摘The main purpose of this paper is to establish the HSrmander-Mihlin type theorem for Fourier multipliers with optimal smoothness on k-parameter Hardy Spaces for k≥ 3 using the multi- parameter Littlewood-Paley theory. For the sake of convenience and simplicity, we only consider the case k 3, and the method works for all the cases k ≥ 3： Tmf（x1,x2,x3） =1/（（2π）＋n1＋n2＋n3） ∫ R n1×R n2×R n3 m（ξ）f（ξ）e 2π ix.ξ dξ. where x = （x1,x2,x3） ∈ Rn1 × Rn2 × R n3 and ξ = （ξ1,ξ2,ξ3） ∈ R n1 × Rn2 ×R n3. One of our main results is the following： Assume that m（ξ） is a function on Rn1＋n2＋n3 satisfying sup j,k,l ∈Z ｜｜mj,k,l｜｜ W（s1,s2,s3）〈∞ with si 〉 ni（1/p-1/2） for 1 ≤ i ≤ 3. Then Tm is bounded from HP（R n1 × R n2 ×R n3） to HP（R n1 ×R n2 × R n3） for all 0 〈 p ≤ 1 and ｜｜Tm｜｜ Hp→Hp≤ sup j,k,l∈Z ｜｜mj,k,l｜｜ W（s1,s2,s3） Moreover, the smoothness assumption on sl for 1 ≤ i ≤ 3 is optimal. Here we have used the notations mj,k,l （ξ）= m（2 j ξ1,2 k ξ2, 2 l ξ3） ψ（ξ1） ψ（ξ2） ψ（ξ3） and ψ（ξi） is a suitable cut-off function on R ni for 1 ≤ i ≤ 3, and W（s1,s2,s3） is a three-parameter Sobolev space on R n × R n2 × Rn 3. Because the Fefferman criterion breaks down in three parameters or more, we consider the Lp boundedness of the Littlewood-Paley square function of T mf to establish its boundedness on the multi-parameter Hardy spaces.
基金supported by the National Science Foundation of USA (Grant Nos. DMS1503612 (Lanzani) and DMS-1265524 (Stein))
文摘The purpose of this paper is to complement the results by Lanzani and Stein(2017) by showing the dense definability of the Cauchy-Leray transform for the domains that give the counter-examples of Lanzani and Stein(2017), where L^p-boundedness is shown to fail when either the "near" C^2 boundary regularity, or the strong C-linear convexity assumption is dropped.
文摘We consider the problem of minimizing the average of a large number of smooth component functions over one smooth inequality constraint.We propose and analyze a stochastic Moving Balls Approximation(SMBA)method.Like stochastic gradient(SG)met hods,the SMBA method's iteration cost is independent of the number of component functions and by exploiting the smoothness of the constraint function,our method can be easily implemented.Theoretical and computational properties of SMBA are studied,and convergence results are established.Numerical experiments indicate that our algorithm dramatically outperforms the existing Moving Balls Approximation algorithm(MBA)for the structure of our problem.
