• Title/Summary/Keyword: approximate duality

Search Result 4, Processing Time 0.02 seconds

BESSEL MULTIPLIERS AND APPROXIMATE DUALS IN HILBERT C -MODULES

  • Azandaryani, Morteza Mirzaee
    • Journal of the Korean Mathematical Society
    • /
    • v.54 no.4
    • /
    • pp.1063-1079
    • /
    • 2017
  • Two standard Bessel sequences in a Hilbert $C^*$-module are approximately duals if the distance (with respect to the norm) between the identity operator on the Hilbert $C^*$-module and the operator constructed by the composition of the synthesis and analysis operators of these Bessel sequences is strictly less than one. In this paper, we introduce (a, m)-approximate duality using the distance between the identity operator and the operator defined by multiplying the Bessel multiplier with symbol m by an element a in the center of the $C^*$-algebra. We show that approximate duals are special cases of (a, m)-approximate duals and we generalize some of the important results obtained for approximate duals to (a, m)-approximate duals. Especially we study perturbations of (a, m)-approximate duals and (a, m)-approximate duals of modular Riesz bases.

Conservative Quadratic RSM combined with Incomplete Small Composite Design and Conservative Least Squares Fitting

  • Kim, Min-Soo;Heo, Seung-Jin
    • Journal of Mechanical Science and Technology
    • /
    • v.17 no.5
    • /
    • pp.698-707
    • /
    • 2003
  • A new quadratic response surface modeling method is presented. In this method, the incomplete small composite design (ISCD) is newly proposed to .educe the number of experimental runs than that of the SCD. Unlike the SCD, the proposed ISCD always gives a unique design assessed on the number of factors, although it may induce the rank-deficiency in the normal equation. Thus, the singular value decomposition (SVD) is employed to solve the normal equation. Then, the duality theory is used to newly develop the conservative least squares fitting (CONFIT) method. This can directly control the ever- or the under-estimation behavior of the approximate functions. Finally, the performance of CONFIT is numerically shown by comparing its'conservativeness with that of conventional fitting method. Also, optimizing one practical design problem numerically shows the effectiveness of the sequential approximate optimization (SAO) combined with the proposed ISCD and CONFIT.

Study on Continuous Nearest Neighbor Query on Trajectory of Moving Objects (이동객체의 궤적에 대한 연속 최근접 질의에 관한 연구)

  • Chung, Ji-Moon
    • Journal of Digital Convergence
    • /
    • v.3 no.1
    • /
    • pp.149-163
    • /
    • 2005
  • Researches for NN(nearest neighbor) query which is often used in LBS system, have been worked. However. Conventional NN query processing techniques are usually meaningless in moving object management system for LBS since their results may be invalidated as soon as the query and data objects move. To solve these problems, in this paper we propose a new nearest neighbor query processing technique, called CTNN, which is possible to meet continuous trajectory nearest neighbor query processing. The proposed technique consists of Approximate CTNN technique which has quick response time, and Exact CTNN technique which makes it possible to search accurately nearest neighbor objects. Experimental results using GSTD datasets shows that the Exact CTNN technique has high accuracy, but has a little low performance for response time. They also shows that the Approximate CTNN technique has low accuracy comparing with the Exact CTNN, but has high response time.

  • PDF

Sequential Approximate Optimization by Dual Method Based on Two-Point Diagonal Quadratic Approximation (이점 대각 이차 근사화 기법을 쌍대기법에 적용한 순차적 근사 최적설계)

  • Park, Seon-Ho;Jung, Sang-Jin;Jeong, Seung-Hyun;Choi, Dong-Hoon
    • Transactions of the Korean Society of Mechanical Engineers A
    • /
    • v.35 no.3
    • /
    • pp.259-266
    • /
    • 2011
  • We present a new dual sequential approximate optimization (SAO) algorithm called SD-TDQAO (sequential dual two-point diagonal quadratic approximate optimization). This algorithm solves engineering optimization problems with a nonlinear objective and nonlinear inequality constraints. The two-point diagonal quadratic approximation (TDQA) was originally non-convex and inseparable quadratic approximation in the primal design variable space. To use the dual method, SD-TDQAO uses diagonal quadratic explicit separable approximation; this can easily ensure convexity and separability. An important feature is that the second-derivative terms of the quadratic approximation are approximated by TDQA, which uses only information on the function and the derivative values at two consecutive iteration points. The algorithm will be illustrated using mathematical and topological test problems, and its performance will be compared with that of the MMA algorithm.