887 resultados para Kernel polynomials


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In this paper we give a new characterization of the closure of the set of the real parts of the zeros of a particular class of Dirichlet polynomials that is associated with the set of dimensions of fractality of certain fractal strings. We show, for some representative cases of nonlattice Dirichlet polynomials, that the real parts of their zeros are dense in their associated critical intervals, confirming the conjecture and the numerical experiments made by M. Lapidus and M. van Frankenhuysen in several papers.

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In this paper we provide the proof of a practical point-wise characterization of the set RP defined by the closure set of the real projections of the zeros of an exponential polynomial P(z) = Σn j=1 cjewjz with real frequencies wj linearly independent over the rationals. As a consequence, we give a complete description of the set RP and prove its invariance with respect to the moduli of the c′ js, which allows us to determine exactly the gaps of RP and the extremes of the critical interval of P(z) by solving inequations with positive real numbers. Finally, we analyse the converse of this result of invariance.

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kdens produces univariate kernel density estimates and graphs the result. kdens supplements official Stata's kdensity. Important additions are: adaptive (i.e. variable bandwidth) kernel density estimation, several automatic bandwidth selectors including the Sheather-Jones plug-in estimator, pointwise variability bands and confidence intervals, boundary correction for variables with bounded domain, fast binned approximation estimation. Note that the moremata package, also available from SSC, is required.

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"February 1980."

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"Supported in part by contract U.S. AEC AT(11-1) 1469 and grant NSF-6J-217".

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"C00-1469-0154."

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Bibliography: p. 24.

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"(This is being submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Mathematics, June 1959.)"

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We give a detailed exposition of the theory of decompositions of linearised polynomials, using a well-known connection with skew-polynomial rings with zero derivative. It is known that there is a one-to-one correspondence between decompositions of linearised polynomials and sub-linearised polynomials. This correspondence leads to a formula for the number of indecomposable sub-linearised polynomials of given degree over a finite field. We also show how to extend existing factorisation algorithms over skew-polynomial rings to decompose sub-linearised polynomials without asymptotic cost.

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An increase in the production of palm kernel meal (PKM) coupled with the concern for continued availability of conventional feedstuffs in some parts of the world has led to research to establish the maximum inclusion level of palm kernel meal in broiler diets. The results suggested that palm kernel meal has no anti-nutritional properties and thus its inclusion is safe up to at least 40% in the diet, provided the diet is balanced in amino acids and metabolisable energy. Although feed digestibility is decreased due to high dietary fibre when PKM is included in the diet, the feed intake is increased. This makes total digestible nutrient intake relatively high. beta-mannan is the main component of palm kernel meal non-starch polysaccharide (NSP). Both mannose and manno-oligosaccharides have been reported to act as prebiotics. The inclusion of palm kernel meal in the diet improves the immune system of birds and reduces pathogenic bacteria and increases the population of nonpathogenic bacteria in the intestine. These two benefits should be considered as strong recommendations for using palm kernel meal in broiler diets, particularly in palm kernel meal producing countries, not only for increasing bird productivity but also to improve chicken health. Selective enzyme addition increases feed efficiency and digestibility as well as decreasing the moisture content of faeces.

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This paper investigates the performance analysis of separation of mutually independent sources in nonlinear models. The nonlinear mapping constituted by an unsupervised linear mixture is followed by an unknown and invertible nonlinear distortion, are found in many signal processing cases. Generally, blind separation of sources from their nonlinear mixtures is rather difficult. We propose using a kernel density estimator incorporated with equivariant gradient analysis to separate the sources with nonlinear distortion. The kernel density estimator parameters of which are iteratively updated to minimize the output independence expressed as a mutual information criterion. The equivariant gradient algorithm has the form of nonlinear decorrelation to perform the convergence analysis. Experiments are proposed to illustrate these results.