Results 221 to 230 of about 8,931 (261)
Some of the next articles are maybe not open access.
Marcinkiewicz integral with rough kernels
Frontiers of Mathematics in China, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Shanzhen Lu
exaly +3 more sources
Vector-valued singular integral operators with rough kernels
Mathematische Nachrichten, 2023AbstractIn this paper, we establish a weak‐type (1,1) boundedness criterion for vector‐valued singular integral operators with rough kernels. As applications, we obtain weak‐type (1,1) bounds for the convolution singular integral operator taking value in the Banach space Y with a rough kernel, the maximal operator taking vector value in Y with a rough ...
Xudong Lai
exaly +3 more sources
Singular Integrals With Rough Kernels
Canadian Mathematical Bulletin, 2004AbstractIn this paper we establish the Lp boundedness of a class of singular integrals with rough kernels associated to polynomial mappings.
Al-Salman, Ahmad, Pan, Yibiao
openaire +2 more sources
On Marcinkiewicz Integral Operators with Rough Kernels
Integral Equations and Operator Theory, 2005This paper is devoted to the study on the L p -mapping properties of Marcinkiewicz integral operators with rough kernels along “polynomial curves” on $$\mathbb{R}^n .$$ The
Huoxiong Wu
exaly +3 more sources
Certain Operators with Rough Singular Kernels
Canadian Journal of Mathematics, 2003AbstractWe study the singular integral operatordefined on all test functions f, where b is a bounded function, α ≥ 0, Ω (yʻ) is an integrable function on the unit sphere Sn-1 satisfying certain cancellation conditions. We prove that, for 1 < p < ∞, TΩ,α extends to a bounded operator from the Sobolev space to the Lebesgue space Lp with Ω being a ...
Chen, Jiecheng +2 more
openaire +1 more source
Multilinear Singular Integrals with Rough Kernel
Acta Mathematica Sinica, English Series, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lu, Shan Zhen, Wu, Huo Xiong, Zhang, Pu
openaire +2 more sources
Kernelized Fuzzy Rough Sets and Their Applications
IEEE Transactions on Knowledge and Data Engineering, 2011Kernel machines and rough sets are two classes of commonly exploited learning techniques. Kernel machines enhance traditional learning algorithms by bringing opportunities to deal with nonlinear classification problems, rough sets introduce a human-focused way to deal with uncertainty in learning problems.
Qinghua Hu +3 more
openaire +2 more sources
On commutators of Marcinkiewicz integrals with rough kernel
Journal of Mathematical Analysis and Applications, 2002 Let \(h(t)\) be a bounded function on \(\mathbb{R}^+\) and \(b\) a function in the \(\text{BMO}(\mathbb{R}^n)\) space. In this paper, the authors consider the higher-order commutator \(\mu^m_{\Omega,b}(f)\) of the Marcinkiewicz integral defined by \[ \mu^m_{\Omega,b}(f)(x)= \Biggl\{\int^\infty_0|F^m_{t, b}(x)|^2 t^{-3} dt\Biggr\}^{1/2}, \] where \[ F ...
Shanzhen Lu
exaly +3 more sources
2009
Kernel machines and rough sets are two classes of popular learning techniques. Kernel machines enhance traditional linear learning algorithms to deal with nonlinear domains by a nonlinear mapping, while rough sets introduce a human-like manner to deal with uncertainty in learning.
Qinghua Hu +3 more
openaire +1 more source
Kernel machines and rough sets are two classes of popular learning techniques. Kernel machines enhance traditional linear learning algorithms to deal with nonlinear domains by a nonlinear mapping, while rough sets introduce a human-like manner to deal with uncertainty in learning.
Qinghua Hu +3 more
openaire +1 more source
Applications of Boolean Kernels in Rough Sets
2014Rough Sets (RS) and Support Vector Machine (SVM) are the two big and independent research areas in AI. Originally, rough set theory is dealing with the concept approximation problem under uncertainty. The basic idea of RS is related to lower and upper approximations, and it can be applied in classification problem.
Sinh Hoa Nguyen, Hung Son Nguyen
openaire +1 more source