• Title/Summary/Keyword: Moore-Penrose inverse

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PERTURBATION ANALYSIS OF THE MOORE-PENROSE INVERSE FOR A CLASS OF BOUNDED OPERATORS IN HILBERT SPACES

  • Deng, Chunyuan;Wei, Yimin
    • Journal of the Korean Mathematical Society
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    • v.47 no.4
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    • pp.831-843
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    • 2010
  • Let $\cal{H}$ and $\cal{K}$ be Hilbert spaces and let T, $\tilde{T}$ = T + ${\delta}T$ be bounded operators from $\cal{H}$ into $\cal{K}$. In this article, two facts related to the perturbation bounds are studied. The first one is to find the upper bound of $\parallel\tilde{T}^+\;-\;T^+\parallel$ which extends the results obtained by the second author and enriches the perturbation theory for the Moore-Penrose inverse. The other one is to develop explicit representations of projectors $\parallel\tilde{T}\tilde{T}^+\;-\;TT^+\parallel$ and $\parallel\tilde{T}^+\tilde{T}\;-\;T^+T\parallel$. In addition, some spectral cases related to these results are analyzed.

CONDITION NUMBERS WITH THEIR CONDITION NUMBERS FOR THE WEIGHTED MOORE-PENROSE INVERSE AND THE WEIGHTED LEAST SQUARES SOLUTION

  • Kang Wenhua;Xiang Hua
    • Journal of applied mathematics & informatics
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    • v.22 no.1_2
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    • pp.95-112
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    • 2006
  • In this paper, the authors investigate the condition number with their condition numbers for weighted Moore-Penrose inverse and weighted least squares solution of min /Ax - b/M, where A is a rank-deficient complex matrix in $C^{m{\times}n} $ and b a vector of length m in $C^m$, x a vector of length n in $C^n$. For the normwise condition number, the sensitivity of the relative condition number itself is studied, the componentwise perturbation is also investigated.

Parameter Optimization of Extreme Learning Machine Using Bacterial Foraging Algorithm (Bacterial Foraging Algorithm을 이용한 Extreme Learning Machine의 파라미터 최적화)

  • Cho, Jae-Hoon;Lee, Dae-Jong;Chun, Myung-Geun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.6
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    • pp.807-812
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    • 2007
  • Recently, Extreme learning machine(ELM), a novel learning algorithm which is much faster than conventional gradient-based learning algorithm, was proposed for single-hidden-layer feedforward neural networks. The initial input weights and hidden biases of ELM are usually randomly chosen, and the output weights are analytically determined by using Moore-Penrose(MP) generalized inverse. But it has the difficulties to choose initial input weights and hidden biases. In this paper, an advanced method using the bacterial foraging algorithm to adjust the input weights and hidden biases is proposed. Experiment at results show that this method can achieve better performance for problems having higher dimension than others.

RIGHT AND LEFT QUOTIENT OF TWO BOUNDED OPERATORS ON HILBERT SPACES

  • Benharrat, Mohammed
    • Communications of the Korean Mathematical Society
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    • v.35 no.2
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    • pp.547-563
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    • 2020
  • We define a left quotient as well as a right quotient of two bounded operators between Hilbert spaces, and we parametrize these two concepts using the Moore-Penrose inverse. In particular, we show that the adjoint of a left quotient is a right quotient and conversely. An explicit formulae for computing left (resp. right) quotient which correspond to adjoint, sum, and product of given left (resp. right) quotient of two bounded operators are also shown.

COMPLETIONS OF HANKEL PARTIAL CONTRACTIONS OF SIZE 5×5 NON-EXTREMAL CASE

  • Lee, Sang Hoon
    • Journal of the Chungcheong Mathematical Society
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    • v.29 no.1
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    • pp.137-150
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    • 2016
  • We introduce a new approach that allows us to solve, algorithmically, the contractive completion problem. In this article, we provide concrete necessary and sufficient conditions for the existence of contractive completions of Hankel partial contractions of size $4{\times}4$ using a Moore-Penrose inverse of a matrix.

A Study on the Shape Analysis Method of Plane Truss Structures under the Prescribed Displacement (변위제약을 받는 평면트러스 구조물의 형태해석기법에 관한 연구)

  • 문창훈;한상을
    • Computational Structural Engineering
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    • v.11 no.1
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    • pp.217-226
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    • 1998
  • The purpose of this study is to develop a technique for the shape analysis of plane truss structures under prescribed displacement modes. The shape analysis is performed based on the existence theorem of the solution and the Moore-Penrose generalized inverse matrix. In this paper, the homologous deformation of structures was proposed as prescribed displacement modes, the shape of the structure is determined from these various modes and applied loads. In general, the shape analysis is a kind of inverse problem different from stress analysis, and the governing equation becomes nonlinear. In this regard, Newton-Raphson method was used to solve the nonlinear equation. Three different shape models are investigated as numerical examples to show the accuracy and the effectiveness of the proposed method.

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HIGHER ORDER ITERATIONS FOR MOORE-PENROSE INVERSES

  • Srivastava, Shwetabh;Gupta, D.K.
    • Journal of applied mathematics & informatics
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    • v.32 no.1_2
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    • pp.171-184
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    • 2014
  • A higher order iterative method to compute the Moore-Penrose inverses of arbitrary matrices using only the Penrose equation (ii) is developed by extending the iterative method described in [1]. Convergence properties as well as the error estimates of the method are studied. The efficacy of the method is demonstrated by working out four numerical examples, two involving a full rank matrix and an ill-conditioned Hilbert matrix, whereas, the other two involving randomly generated full rank and rank deficient matrices. The performance measures are the number of iterations and CPU time in seconds used by the method. It is observed that the number of iterations always decreases as expected and the CPU time first decreases gradually and then increases with the increase of the order of the method for all examples considered.

COMPUTING GENERALIZED INVERSES OF A RATIONAL MATRIX AND APPLICATIONS

  • Stanimirovic, Predrag S.;Karampetakis, N. P.;Tasic, Milan B.
    • Journal of applied mathematics & informatics
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    • v.24 no.1_2
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    • pp.81-94
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    • 2007
  • In this paper we investigate symbolic implementation of two modifications of the Leverrier-Faddeev algorithm, which are applicable in computation of the Moore-Penrose and the Drazin inverse of rational matrices. We introduce an algorithm for computation of the Drazin inverse of rational matrices. This algorithm represents an extension of the papers [11] and [14]. and a continuation of the papers [15, 16]. The symbolic implementation of these algorithms in the package MATHEMATICA is developed. A few matrix equations are solved by means of the Drazin inverse and the Moore-Penrose inverse of rational matrices.

A DFT Deblurring Algorithm of Blind Blur Image (무정보 blur 이미지 복구를 위한 DFT 변환)

  • Moon, Kyung-Il;Kim, Chul
    • Journal of The Korean Association of Information Education
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    • v.15 no.3
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    • pp.517-524
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    • 2011
  • This paper presents a fast blind deconvolution method that produces a deblurring result from a single image in only a few seconds. The high speed of our method is enabled by considering the Discrete Fourier Transform (DFT), and its relation to filtering and convolution, and fast computation of Moore-Penrose inverse matrix. How can we predict the behavior of an arbitrary filter, or even more to the point design a filter to achieve certain specifications. The idea is to study the frequency response of the filter. This concept leads to an useful convolution formula. A Matlab implementation of our method usually takes less than one minute to deblur an image of moderate size, while the deblurring quality is comparable.

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SINGULAR INTEGRAL EQUATIONS AND UNDERDETERMINED SYSTEMS

  • KIM, SEKI
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.2 no.2
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    • pp.67-80
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    • 1998
  • In this paper the linear algebraic system obtained from a singular integral equation with variable coeffcients by a quadrature-collocation method is considered. We study this underdetermined system by means of the Moore Penrose generalized inverse. Convergence in compact subsets of [-1, 1] can be shown under some assumptions on the coeffcients of the equation.

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