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Double weighted mean methods equivalent to $(C,1,1)$
Publicationes Mathematicae Debrecen, 1995Summary: We establish sufficient conditions for the double weighted mean matrices \((\overline N, p_{ij})\) and \((C,1,1)\), the double Cesàro matrix of order \((1,1)\), to be equivalent and absolutely equivalent of order \(k \geq 1\). The latter equivalence is proved only in the case where \(\{p_{ij}\}\) is factorable.
Móricz, F., Rhoades, B. E.
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On Absolute Weighted Mean Summability Methods
Bulletin of the London Mathematical Society, 1993The author proved the factor theorem for \(| C,1|_ k \Rightarrow | \overline{N}, p_ n|_ k\), \(k\geq 1\) and \(| \overline{N}, p_ n|_ k \Rightarrow | C,1|_ k\), \(k\geq 1\) under the conditions (i) \(np_ n= O(P_ n)\) and (ii) \(P_ n= O(np_ n)\). \textit{M. A. Sarigöl} [Indian J. Pure Appl. Math. 22, No.
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Extended Tauberian Theorem for the weighted mean Method of Summability
Ukrainian Mathematical Journal, 2013The authors provide some Tauberian-like conditions using the weighted mean summability method to obtain information about the asymptotic behavior, e.g., slow oscillation, of a real sequence. Once slow oscillation is established, some classical results can easily be established as a corollary to this theorem.
Canak, I., Totur, U.
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A Tauberian theorem for discrete weighted mean methods
Analysis, 2006A Tauberian theorem of “slowly decreasing” type is proved for discrete weighted mean methods of summability by reduction to the corresponding Tauberian theorem for weighted mean methods.
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Classifier selection method based on clustering and weighted mean
Journal of Intelligent & Fuzzy Systems, 2016Currently, Multiple Classifier System (MCS) attracts more and more attentions and has become one of the research hotspots in the pattern recognition field. Classifier selection is a commonly used strategy for MCS to achieve the final decision. A classifier selection method based on clustering and weighted mean is proposed in this paper.
Mi, Aizhong, Sima, Haifeng
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The Nörlund and The Weighted Mean Methods
2015In this chapter, we introduce the Norlund and the Weighted Mean methods in the ultrametric set-up and their properties are elaborately discussed. We also show that the Mazur–Orlicz theorem and Brudno’s theorem fail to hold in the ultrametric case.
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Attribute subset selection by mixed weighting mean classification method
2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), 2016The discovery of knowledge from the huge available data is the highest mount setback in practical pattern classification and knowledge discovery problem. The preprocessing of data plays a major role in knowledge discovery as it consequently improves the accuracy of the classifier.
Adidela Daveedu Raju +2 more
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Some weighted quadrature methods based upon the mean value theorems
Mathematical Methods in the Applied Sciences, 2020In this paper, a class of weighted quadrature methods is introduced for smooth functions based upon the use of the mean value theorems. These new quadrature rules are also treated in a systematic approach involving formal series expansion. The convergence analysis of the proposed method is studied here for both the non‐weighted and the weighted cases ...
Herbert H. H. Homeier +3 more
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