• Honam Mathematical Journal
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• v.40 no.4
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• pp.765-770
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• 2018

In this paper, we investigate the majorization properties for certain subclasses of analytic functions of complex order. Moreover, some interesting consequences of our main theorem are pointed out.

• East Asian mathematical journal
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• v.17 no.2
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• pp.175-183
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• 2001

The main object of this paper is to investigate several majorization problems involving two subclasses $S_{p,q}(\gamma)$ and $C_{p,q}(\gamma)$ of p-valently starlike and p-valently convex functions of complex order ${\gamma}{\neq}0$ in the open unit disk $\mathbb{u}$. Relevant connections of the results presented here with those given by earlier workers on the subject are also indicated.

• Nonlinear Functional Analysis and Applications
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• v.26 no.1
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• pp.71-81
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• 2021

The main object of this present paper is to study some majorization problems for certain classes of analytic functions defined by means of q-calculus operator associated with exponential function.

• East Asian mathematical journal
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• v.24 no.1
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• pp.67-79
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• 2008

In this paper, we characterize the chaotic operator order $A\;{\gg}\;C\;{\gg}\;B$. Consequently all other possible characterizations follow easily. Some satellite theorems of the Furuta inequality are naturally given. And finally, using results of characterizing $A\;{\gg}\;C\;{\gg}\;B$, and by the Douglas's majorization and factorization theorem we are able to characterize the chaotic operator order $A\;{\gg}\;B$ in terms of operator equalities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.10
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• pp.3084-3108
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• 2024

The previous graph-based estimation algorithm is of poor performance in low signal-to-noise ratio (SNR) and is failure for frequency band signals. An improved graph-based SNR estimator using blocking sum of spectrum of the observed signal is proposed in this article, which consists of two stages: fitting the SNR estimation expression by training samples and estimating the SNR of the test signal. In the former stage, the training samples are firstly segmented with overlap, then the real part of the spectrum of each segment is blocked without overlap and summed to be transformed to a graph, and accordingly the average degree sum (DS) of the graphs is calculated. Afterwards, a nonlinear fitting of the relationship between the average DS and the SNR is obtained using a trust region fitting algorithm. In the latter stage, the average DS of the test signal is obtained by applying the mentioned scheme. Subsequently, substitute it into the fitted expression to estimate the SNR. Moreover, we analyze the impact mechanism of the order preserving between the majorization order of input samples and the majorization order of vertex probability vectors, which providing a basis for the interpretability of graph-based SNR estimator and for the selection of input forms for graph transform in the estimation. Simulation results demonstrate that the proposed algorithm has a superiority performance for both baseband and frequency band signals under low SNR and multipath or fading channels, with a computational complexity of approximately 50% compared to the existing graph-based algorithm.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1987.10a
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• pp.35-35
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• 1987

Consider a job shop that is modelled as an open queueing network of the Jackson(l957) type. All work stations in the shop have the same number of parallel servers. Two problems are studied : the loading of stations and the assignment of servers, which are represented by loading and assingment vectors, respectively. Ma jorization and arrangement orderings are established to order, respectively, the loading and the assignment vectors. It is shown that reducing the loading vector under ma jorizat ion or increasing the assignment vector under arrangement ordering will reduce the congestion in the shop in terms of reducing the total number of jobs(in the sense of likelihood ratio ordering), the maximum queue length(in the sense of stochastic ordering), and the queue-length vector( in the sense of stochastic majorization). The results can be used to supprot production planning in certain job shops, and to aid the desing of storage capacity. (OPEN QUEUEING NETWORK; WJORIZATION; ARRANGEMENT ORDERINC; LIKELIHOOD RATIO ORDERINC; STOCHASTIC ORDERING)