• Title/Summary/Keyword: Singular Vector

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QUANTITATIVE WEIGHTED BOUNDS FOR THE VECTOR-VALUED SINGULAR INTEGRAL OPERATORS WITH NONSMOOTH KERNELS

  • Hu, Guoen
    • Bulletin of the Korean Mathematical Society
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    • v.55 no.6
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    • pp.1791-1809
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    • 2018
  • Let T be the singular integral operator with nonsmooth kernel which was introduced by Duong and McIntosh, and $T_q(q{\in}(1,{\infty}))$ be the vector-valued operator defined by $T_qf(x)=({\sum}_{k=1}^{\infty}{\mid}T\;f_k(x){\mid}^q)^{1/q}$. In this paper, by proving certain weak type endpoint estimate of L log L type for the grand maximal operator of T, the author establishes some quantitative weighted bounds for $T_q$ and the corresponding vector-valued maximal singular integral operator.

WEIGHTED ESTIMATES FOR CERTAIN ROUGH OPERATORS WITH APPLICATIONS TO VECTOR VALUED INEQUALITIES

  • Liu, Feng;Xue, Qingying
    • Journal of the Korean Mathematical Society
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    • v.58 no.4
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    • pp.1035-1058
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    • 2021
  • Under certain rather weak size conditions assumed on the kernels, some weighted norm inequalities for singular integral operators, related maximal operators, maximal truncated singular integral operators and Marcinkiewicz integral operators in nonisotropic setting will be shown. These weighted norm inequalities will enable us to obtain some vector valued inequalities for the above operators.

SINGULAR MINIMAL TRANSLATION GRAPHS IN EUCLIDEAN SPACES

  • Aydin, Muhittin Evren;Erdur, Ayla;Ergut, Mahmut
    • Journal of the Korean Mathematical Society
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    • v.58 no.1
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    • pp.109-122
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    • 2021
  • In this paper, we consider the problem of finding the hypersurface Mn in the Euclidean (n + 1)-space ℝn+1 that satisfies an equation of mean curvature type, called singular minimal hypersurface equation. Such an equation physically characterizes the surfaces in the upper half-space ℝ+3 (u) with lowest gravity center, for a fixed unit vector u ∈ ℝ3. We first state that a singular minimal cylinder Mn in ℝn+1 is either a hyperplane or a α-catenary cylinder. It is also shown that this result remains true when Mn is a translation hypersurface and u is a horizantal vector. As a further application, we prove that a singular minimal translation graph in ℝ3 of the form z = f(x) + g(y + cx), c ∈ ℝ - {0}, with respect to a certain horizantal vector u is either a plane or a α-catenary cylinder.

WEIGHTED ESTIMATES FOR CERTAIN ROUGH SINGULAR INTEGRALS

  • Zhang, Chunjie
    • Journal of the Korean Mathematical Society
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    • v.45 no.6
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    • pp.1561-1576
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    • 2008
  • In this paper we shall prove some weighted norm inequalities of the form $${\int}_{R^n}\;|Tf(x)|^pu(x)dx\;{\leq}\;C_p\;{\int}_{R^n}\;|f(x)|^pNu(x)dx$$ for certain rough singular integral T and maximal singular integral $T^*$. Here u is a nonnegative measurable function on $R^n$ and N denotes some maximal operator. As a consequence, some vector valued inequalities for both T and $T^*$ are obtained. We shall also get a boundedness result of T on the Triebel-Lizorkin spaces.

GEOMETRIC AND APPROXIMATION PROPERTIES OF GENERALIZED SINGULAR INTEGRALS IN THE UNIT DISK

  • Anastassiou George A.;Gal Sorin G.
    • Journal of the Korean Mathematical Society
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    • v.43 no.2
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    • pp.425-443
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    • 2006
  • The aim of this paper is to obtain several results in approximation by Jackson-type generalizations of complex Picard, Poisson-Cauchy and Gauss-Weierstrass singular integrals in terms of higher order moduli of smoothness. In addition, these generalized integrals preserve some sufficient conditions for starlikeness and univalence of analytic functions. Also approximation results for vector-valued functions defined on the unit disk are given.

An Watermarking Method based on Singular Vector Decomposition and Vector Quantization using Fuzzy C-Mean Clustering (특이치 분해와 Fuzzy C-Mean(FCM) 군집화를 이용한 벡터양자화에 기반한 워터마킹 방법)

  • Lee, Byeong-Hui;Jang, U-Seok;Gang, Hwan-Il
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.11a
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    • pp.267-271
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    • 2007
  • 본 논문은 원본이미지와 은닉이미지의 좋은 압축률과 만족할만한 이미지의 질, 그리고 외부공격에 강인한 이미지은닉의 한 방법으로 특이치 분해와 퍼지 군집화를 이용한 벡터양자화를 이용한 워터마킹 방법을 소개하였다. 실험에서는 은닉된 이미지의 비가시성과 외부공격에 대한 강인성을 증명하였다.

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WEIGHTED VECTOR-VALUED BOUNDS FOR A CLASS OF MULTILINEAR SINGULAR INTEGRAL OPERATORS AND APPLICATIONS

  • Chen, Jiecheng;Hu, Guoen
    • Journal of the Korean Mathematical Society
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    • v.55 no.3
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    • pp.671-694
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    • 2018
  • In this paper, we investigate the weighted vector-valued bounds for a class of multilinear singular integral operators, and its commutators, from $L^{p_1}(l^{q_1};\;{\mathbb{R}}^n,\;w_1){\times}{\cdots}{\times}L^{p_m}(l^{q_m};\;{\mathbb{R}}^n,\;w_m)$ to $L^p(l^q;\;{\mathbb{R}}^n,\;{\nu}_{\vec{w}})$, with $p_1,{\cdots},p_m$, $q_1,{\cdots},q_m{\in}(1,\;{\infty})$, $1/p=1/p_1+{\cdots}+1/p_m$, $1/q=1/q_1+{\cdots}+1/q_m$ and ${\vec{w}}=(w_1,{\cdots},w_m)$ a multiple $A_{\vec{P}}$ weights. Our argument also leads to the weighted weak type endpoint estimates for the commutators. As applications, we obtain some new weighted estimates for the $Calder{\acute{o}}n$ commutator.

A Text Similarity Measurement Method Based on Singular Value Decomposition and Semantic Relevance

  • Li, Xu;Yao, Chunlong;Fan, Fenglong;Yu, Xiaoqiang
    • Journal of Information Processing Systems
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    • v.13 no.4
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    • pp.863-875
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    • 2017
  • The traditional text similarity measurement methods based on word frequency vector ignore the semantic relationships between words, which has become the obstacle to text similarity calculation, together with the high-dimensionality and sparsity of document vector. To address the problems, the improved singular value decomposition is used to reduce dimensionality and remove noises of the text representation model. The optimal number of singular values is analyzed and the semantic relevance between words can be calculated in constructed semantic space. An inverted index construction algorithm and the similarity definitions between vectors are proposed to calculate the similarity between two documents on the semantic level. The experimental results on benchmark corpus demonstrate that the proposed method promotes the evaluation metrics of F-measure.

A New Support Vector Compression Method Based on Singular Value Decomposition

  • Yoon, Sang-Hun;Lyuh, Chun-Gi;Chun, Ik-Jae;Suk, Jung-Hee;Roh, Tae-Moon
    • ETRI Journal
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    • v.33 no.4
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    • pp.652-655
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    • 2011
  • In this letter, we propose a new compression method for a high dimensional support vector machine (SVM). We used singular value decomposition (SVD) to compress the norm part of a radial basis function SVM. By deleting the least significant vectors that are extracted from the decomposition, we can compress each vector with minimized energy loss. We select the compressed vector dimension according to the predefined threshold which can limit the energy loss to design criteria. We verified the proposed vector compressed SVM (VCSVM) for conventional datasets. Experimental results show that VCSVM can reduce computational complexity and memory by more than 40% without reduction in accuracy when classifying a 20,958 dimension dataset.