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  • 1
    Electronic Resource
    Electronic Resource
    s.l. : American Chemical Society
    Energy & fuels 7 (1993), S. 897-901 
    ISSN: 1520-5029
    Source: ACS Legacy Archives
    Topics: Chemistry and Pharmacology , Energy, Environment Protection, Nuclear Power Engineering , Process Engineering, Biotechnology, Nutrition Technology
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    s.l. : American Chemical Society
    Energy & fuels 7 (1993), S. 902-905 
    ISSN: 1520-5029
    Source: ACS Legacy Archives
    Topics: Chemistry and Pharmacology , Energy, Environment Protection, Nuclear Power Engineering , Process Engineering, Biotechnology, Nutrition Technology
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Aequationes mathematicae 37 (1989), S. 1-14 
    ISSN: 1420-8903
    Keywords: Primary 65H10
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Summary We study linear sequential (adaptive) information for approximating zeros of polynomials of unbounded degree and establish a theorem on constrained approximation of smooth functions by polynomials. For a positive ε we seek a pointx * such that|x * − α p | ⩽ ε, whereα p is a zero of a real polynomialp in the interval [a, b]. We assume thatp belongs to the classF 1 of polynomials of bounded arbitrary seminorm and having a root in [a, b] or to the classF 2 of polynomials which are nonpositive ata, nonnegative atb and have exactly one simple zero in [a, b]. The information onp consists ofn sequential (adaptive) evaluations of arbitrary linear functionals. The pointx * is constructed by means of an algorithm which is an arbitrary mapping depending on the information onp. We show that there exists no information and no algorithm for computingx * for everyp fromF 1, no matter how large the value ofn is. This is a stronger result than that obtained by us for smooth functions. For the classF 2 we can find a pointx * for arbitraryp andε. Anoptimal algorithm, i.e., an algorithm with the smallest error, is thebisection of the smallest known interval containing the root ofp. We also exhibitoptimal information operators, i.e., the linear functionals for which the error of an optimal algorithm that uses them is minimal. It turns out that in the class of nonsequential (parallel) information, i.e., when the functionals are given simultaneously, optimal information consists of the evaluations of a polynomial atn-equidistant points in [a, b]. In the class of sequential continuous information, optimal information consists of evaluations of a polynomial atn points generated by thebisection method. To prove this result we establish a theorem on constrained approximation of smooth functions by polynomials. More precisely, we prove that a smooth function can be arbitrarily well uniformly approximated by a polynomial which satisfies constrains given byn arbitrary continuous linear functionals. Our results indicate that the problem of finding an ε-approximation to a real zero of a real polynomial (of unknown degree) is essentially of the same difficulty as the problem of finding an ε-approximation to a zero of an infinitely differentiable function.
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    Numerische Mathematik 57 (1990), S. 421-433 
    ISSN: 0945-3245
    Keywords: AMS(MOS): 65H10 ; CR: G1.5
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Summary We seek a approximation to a zero of an infinitely differentiable functionf: [0, 1]→ℜ such thatf(0)≦0 andf(1)≧0. It is known that the error of the bisection method usingn function evaluations is 2−(n+1). If the information used are function values, then it is known that bisection information and the bisection algorithm are optimal. Traub and Woźniakowski conjectured in [5] that the bisection information and algorithm are optimal even if far more general information is permitted. They permit adaptive (sequential) evaluations of arbitrary linear functionals and arbitrary transformations of this information as algorithms. This conjecture was established in [2]. That is forn fixed, the bisection information and algorithm are optimal in the worst case setting. Thus nothing is lost by restricting oneself to function values. One may then ask whether bisection is nearly optimal in theasymptotic worst case sense, that is,possesses asymptotically nearly the best rate of convergence. Methods converging fast asymptotically, like Newton or secant type, are of course, widely used in scientific computation. We prove that the answer to this question is positive for the classF of functions having zeros ofinfinite multiplicity and information consisting of evaluations of continuous linear functionals. Assuming that everyf inF has zeroes withbounded multiplicity, there are known hybrid methods which have at least quadratic rate of convergence asn tends to infinity, see e.g., Brent [1], Traub [4] and Sect. 1.
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    Springer
    Numerische Mathematik 39 (1982), S. 405-410 
    ISSN: 0945-3245
    Keywords: AMS(MOS) 65D15 ; CR 5.13
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Summary The problem of finding optimal error quadrature formulas for evaluating $$\int\limits_{ - 1}^1 {f(x)dx} $$ , whereH p and wherep〉1, has been investigated in some recent papers (e.g. [1, 3, 4, 10]). In this paper we study a class of ‘almost optimal’ quadrature formulas which were introduced by Stenger [8–11], for computing the integral $$\int\limits_{w^{ - 1} ([ - 1,1])} {f(z)dz,f \in H_p (D).} $$ . HereD is a simply connected domain in the complex plane ℂ andw is a conformal map ofD onto the unit discU. The cost of our quadratures to obtain an ε-approximation to the above integral is at most twice as much as the cost using the optimal formulas.
    Type of Medium: Electronic Resource
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  • 6
    Electronic Resource
    Electronic Resource
    Springer
    Numerische Mathematik 40 (1982), S. 111-117 
    ISSN: 0945-3245
    Keywords: AMS(MOS): 65H10 ; CR: 5.15
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Summary We seek an approximation to a zero of a continuous functionf:[a,b]→ℝ such thatf(a)≦0 andf(b)≧0. It is known that the bisection algorithm makes optimal use ofn function evaluations, i.e., yields the minimal error which is (b−a)/2 n+1, see e.g. Kung [2]. Traub and Wozniakowski [5] proposed using more general information onf by permitting the adaptive evaluations ofn arbitrary linear functionals. They conjectured [5, p. 170] that the bisection algorithm remains optimal even if these general evaluations are permitted. This paper affirmatively proves this conjecture. In fact we prove optimality of the bisection algorithm even assuming thatf is infinitely many times differentiable on [a, b] and has exactly one simple zero.
    Type of Medium: Electronic Resource
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  • 7
    Electronic Resource
    Electronic Resource
    s.l. ; Stafa-Zurich, Switzerland
    Materials science forum Vol. 377 (June 2001), p. 15-28 
    ISSN: 1662-9752
    Source: Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Type of Medium: Electronic Resource
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  • 8
    Electronic Resource
    Electronic Resource
    Springer
    The visual computer 12 (1996), S. 445-450 
    ISSN: 1432-2315
    Keywords: Key words: Adjacency graph ; Finite element analysis (FEA) data
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Type of Medium: Electronic Resource
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  • 9
    ISSN: 1662-9752
    Source: Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: The aim of the study was to obtain a ferritic-austenitic stainless steel through sintering of the mixture of austenitic steel AISI 316L powders with silicon in the amount ranging from 1 to 7%. The pressed mixtures were sintered at 1240oC for 60 minutes under hydrogen atmosphere. The results of the silicon admixture on the density, porosity, microstructure and mechanical properties of the sintered specimens are discussed
    Type of Medium: Electronic Resource
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  • 10
    Electronic Resource
    Electronic Resource
    Springer
    Numerische Mathematik 43 (1984), S. 225-240 
    ISSN: 0945-3245
    Keywords: AMS(MOS): 65 H 10 ; CR: 5.15
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Summary For a given nonnegative ε we seek a pointx * such that |f(x *)|≦ε wheref is a nonlinear transformation of the cubeB=[0,1] m into ℝ (or ℝ p ,p〉1) satisfying a Lipschitz condition with the constantK and having a zero inB. The information operator onf consists ofn values of arbitrary linear functionals which are computed adaptively. The pointx * is constructed by means of an algorithm which is a mapping depending on the information operator. We find an optimal algorithm, i.e., algorithm with the smallest error, which usesn function evaluations computed adaptively. We also exhibit nearly optimal information operators, i.e., the linear functionals for which the error of an optimal algorithm that uses them is almost minimal. Nearly optimal information operators consists ofn nonadaptive function evaluations at equispaced pointsx j in the cubeB. This result exhibits the superiority of the T. Aird and J. Rice procedure ZSRCH (IMSL library [1]) over Sobol's approach [7] for solving nonlinear equations in our class of functions. We also prove that the simple search algorithm which yields a pointx *=x k such that $$\left| {f(x_k )} \right| = \mathop {\min }\limits_{1 \leqq j \leqq n} \left| {f(x_j )} \right|$$ is nearly optimal. The complexity, i.e., the minimal cost of solving our problem is roughly equal to (K/ε) m .
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