• Title/Summary/Keyword: Hilbert kernel

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SOLUTION OF THE SYSTEM OF FOURTH ORDER BOUNDARY VALUE PROBLEM USING REPRODUCING KERNEL SPACE

  • Akram, Ghazala;Ur Rehman, Hamood
    • Journal of applied mathematics & informatics
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    • v.31 no.1_2
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    • pp.55-63
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    • 2013
  • In this paper, a general technique is proposed for solving a system of fourth-order boundary value problems. The solution is given in the form of series and its approximate solution is obtained by truncating the series. Advantages of the method are that the representation of exact solution is obtained in a new reproducing kernel Hilbert space and accuracy of numerical computation is higher. Numerical results show that the method employed in the paper is valid. Numerical evidence is presented to show the applicability and superiority of the new method.

Truncated Kernel Projection Machine for Link Prediction

  • Huang, Liang;Li, Ruixuan;Chen, Hong
    • Journal of Computing Science and Engineering
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    • v.10 no.2
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    • pp.58-67
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    • 2016
  • With the large amount of complex network data that is increasingly available on the Web, link prediction has become a popular data-mining research field. The focus of this paper is on a link-prediction task that can be formulated as a binary classification problem in complex networks. To solve this link-prediction problem, a sparse-classification algorithm called "Truncated Kernel Projection Machine" that is based on empirical-feature selection is proposed. The proposed algorithm is a novel way to achieve a realization of sparse empirical-feature-based learning that is different from those of the regularized kernel-projection machines. The algorithm is more appealing than those of the previous outstanding learning machines since it can be computed efficiently, and it is also implemented easily and stably during the link-prediction task. The algorithm is applied here for link-prediction tasks in different complex networks, and an investigation of several classification algorithms was performed for comparison. The experimental results show that the proposed algorithm outperformed the compared algorithms in several key indices with a smaller number of test errors and greater stability.

Signal Processing Technology for Rotating Machinery Fault Signal Diagnosis (회전기계 결함신호 진단을 위한 신호처리 기술 개발)

  • Choi, Byeong-Keun;Ahn, Byung-Hyun;Kim, Yong-Hwi;Lee, Jong-Myeong;Lee, Jeong-Hoon
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2013.10a
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    • pp.331-337
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    • 2013
  • Acoustic Emission technique is widely applied to develop the early fault detection system, and the problem about a signal processing method for AE signal is mainly focused on. In the signal processing method, envelope analysis is a useful method to evaluate the bearing problems and Wavelet transform is a powerful method to detect faults occurred on rotating machinery. However, exact method for AE signal is not developed yet. Therefore, in this paper two methods which are Hilbert transform and DET for feature extraction. In addition, we evaluate the classification performance with varying the parameter from 2 to 15 for feature selection DET, 0.01 to 1.0 for the RBF kernel function of SVR, and the proposed algorithm achieved 94% classification accuracy with the parameter of the RBF 0.08, 12 feature selection.

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SZEGÖ PROJECTIONS FOR HARDY SPACES IN QUATERNIONIC CLIFFORD ANALYSIS

  • He, Fuli;Huang, Song;Ku, Min
    • Bulletin of the Korean Mathematical Society
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    • v.59 no.5
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    • pp.1215-1235
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    • 2022
  • In this paper we study Szegö kernel projections for Hardy spaces in quaternionic Clifford analysis. At first we introduce the matrix Szegö projection operator for the Hardy space of quaternionic Hermitean monogenic functions by the characterization of the matrix Hilbert transform in the quaternionic Clifford analysis. Then we establish the Kerzman-Stein formula which closely connects the matrix Szegö projection operator with the Hardy projection operator onto the Hardy space, and we get the matrix Szegö projection operator in terms of the Hardy projection operator and its adjoint. At last, we construct the explicit matrix Szegö kernel function for the Hardy space on the sphere as an example, and get the solution to a Diriclet boundary value problem for matrix functions.

QUALITATIVE UNCERTAINTY PRINCIPLE FOR GABOR TRANSFORM

  • Bansal, Ashish;Kumar, Ajay
    • Bulletin of the Korean Mathematical Society
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    • v.54 no.1
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    • pp.71-84
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    • 2017
  • We discuss the qualitative uncertainty principle for Gabor transform on certain classes of the locally compact groups, like abelian groups, ${\mathbb{R}}^n{\times}K$, K ⋉ ${\mathbb{R}}^n$ where K is compact group. We shall also prove a weaker version of qualitative uncertainty principle for Gabor transform in case of compact groups.

REGULARIZED SOLUTION TO THE FREDHOLM INTEGRAL EQUATION OF THE FIRST KIND WITH NOISY DATA

  • Wen, Jin;Wei, Ting
    • Journal of applied mathematics & informatics
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    • v.29 no.1_2
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    • pp.23-37
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    • 2011
  • In this paper, we use a modified Tikhonov regularization method to solve the Fredholm integral equation of the first kind. Under the assumption that measured data are contaminated with deterministic errors, we give two error estimates. The convergence rates can be obtained under the suitable choices of regularization parameters and the number of measured points. Some numerical experiments show that the proposed method is effective and stable.

ON THE SPECTRAL MAXIMAL SPACES OF A MULTIPLICATION OPERATOR

  • Park, Jae-Chul;Yoo, Jong-Kwang
    • Journal of the Korean Mathematical Society
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    • v.33 no.1
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    • pp.205-216
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    • 1996
  • In [13], Ptak and Vrbova proved that if T is a bounded normal operator T on a complex Hilbert space H, then the ranges of the spectral projections can be represented in the form $$ \varepsilon(F)H = \bigcap_{\lambda\notinF} (T - \lambda I) H for all closed subsets F of C, $$ where $\varepsilon$ denotes the spectral measure associated with T.

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Range Kernel Orthogonality and Finite Operators

  • Mecheri, Salah;Abdelatif, Toualbia
    • Kyungpook Mathematical Journal
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    • v.55 no.1
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    • pp.63-71
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    • 2015
  • Let H be a separable infinite dimensional complex Hilbert space, and let $\mathcal{L}(H)$ denote the algebra of all bounded linear operators on H into itself. Let $A,B{\in}\mathcal{L}(H)$ we define the generalized derivation ${\delta}_{A,B}:\mathcal{L}(H){\mapsto}\mathcal{L}(H)$ by ${\delta}_{A,B}(X)=AX-XB$, we note ${\delta}_{A,A}={\delta}_A$. If the inequality ${\parallel}T-(AX-XA){\parallel}{\geq}{\parallel}T{\parallel}$ holds for all $X{\in}\mathcal{L}(H)$ and for all $T{\in}ker{\delta}_A$, then we say that the range of ${\delta}_A$ is orthogonal to the kernel of ${\delta}_A$ in the sense of Birkhoff. The operator $A{\in}\mathcal{L}(H)$ is said to be finite [22] if ${\parallel}I-(AX-XA){\parallel}{\geq}1(*)$ for all $X{\in}\mathcal{L}(H)$, where I is the identity operator. The well-known inequality (*), due to J. P. Williams [22] is the starting point of the topic of commutator approximation (a topic which has its roots in quantum theory [23]). In [16], the author showed that a paranormal operator is finite. In this paper we present some new classes of finite operators containing the class of paranormal operators and we prove that the range of a generalized derivation is orthogonal to its kernel for a large class of operators containing the class of normal operators.

On Self-commutator Approximants

  • Duggal, Bhagwati Prashad
    • Kyungpook Mathematical Journal
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    • v.49 no.1
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    • pp.1-6
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    • 2009
  • Let B(X) denote the algebra of operators on a complex Banach space X, H(X) = {h ${\in}$ B(X) : h is hermitian}, and J(X) = {x ${\in}$ B(X) : x = $x_1$ + $ix_2$, $x_1$ and $x_2$ ${\in}$ H(X)}. Let ${\delta}_a$ ${\in}$ B(B(X)) denote the derivation ${\delta}_a$ = ax - xa. If J(X) is an algebra and ${\delta}_a^{-1}(0){\subseteq}{\delta}_{a^*}^{-1}(0)$ for some $a{\in}J(X)$, then ${\parallel}a{\parallel}{\leq}{\parallel}a-(x^*x-xx^*){\parallel}$ for all $x{\in}J(X){\cap}{\delta}_a^{-1}(0)$. The cases J(X) = B(H), the algebra of operators on a complex Hilbert space, and J(X) = $C_p$, the von Neumann-Schatten p-class, are considered.

Signal Processing Technology for Rotating Machinery Fault Signal Diagnosis (회전기계 결함신호 진단을 위한 신호처리 기술 개발)

  • Ahn, Byung-Hyun;Kim, Yong-Hwi;Lee, Jong-Myeong;Lee, Jeong-Hoon;Choi, Byeong-Keun
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.24 no.7
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    • pp.555-561
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    • 2014
  • Acoustic Emission technique is widely applied to develop the early fault detection system, and the problem about a signal processing method for AE signal is mainly focused on. In the signal processing method, envelope analysis is a useful method to evaluate the bearing problems and wavelet transform is a powerful method to detect faults occurred on rotating machinery. However, exact method for AE signal is not developed yet for the rotating machinery diagnosis. Therefore, in this paper two methods which are processed by Hilbert transform and DET for feature extraction. In addition, we evaluate the classification performance with varying the parameter from 2 to 15 for feature selection DET, 0.01 to 1.0 for the RBF kernel function of SVR, and the proposed algorithm achieved 94 % classification of averaged accuracy with the parameter of the RBF 0.08, 12 feature selection.