Time filter

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Hua H.,Huaiyin Institute of Technology
Match | Year: 2010

The second geometric-arithmetic index GA 2(G) of a graph G was introduced recently by Fath-Tabar et al. [2] and is defined to be mathematical equation representative wnere e = uv 's one edge in G, and nu(e,G) denotes the number of vertices in G lying closer to u than to v. In this paper, we characterize the tree with the minimum GA% index among the set of trees with given order and diameter. As applications, we deduce the trees with the minimum and second-minimum GA 2 index among the set of trees of given order, respectively. In addition, all the trees minimizing the GA 2 index have been shown to have minimum Szeged index and Wiener index, which deduced a result of [7] concerning the Wiener index of trees with given diameter. Source

Gai R.,Huaiyin Institute of Technology
Asian Journal of Control | Year: 2015

This paper is devoted to studying the issue of modeling, forecasting, and optimal feedback control of discrete-time first-order linear stochastic systems with prospective strong intervention (PSI). First, one type of PSI is formulated. Then, one class of induced mechanisms of PSI is characterized, and, with respect to the induced mechanisms, two multi-step forecasting methods for estimating the occurrence time and terminal time of PSI are discussed. Based on these fundamental results, the problem of optimal control with respect to an improved minimum variance performance index is discussed. Finally, the effectiveness and advantages of the proposed control strategy and approach are verified and demonstrated through numerical simulations. © 2014 Chinese Automatic Control Society and Wiley Publishing Asia Pty Ltd. Source

The objective of Kim (2010) is to give a new delay-dependent full-order robust H∞ filter design method for uncertain discrete-time singular time-delay systems. In the analysis and design procedure, the regularity and absence of impulses of the filtering error system are studied simultaneously. However, an error appeared in the H∞ performance analysis, which is pointed out in this note. © 2015 Elsevier Ltd. All rights reserved. Source

Wang Y.,Huaiyin Institute of Technology
Circuits, Systems, and Signal Processing | Year: 2012

An approach to finding digital differentiator window functions is studied. The frequency response of the truncated ideal differentiator is expressed by two parts. One is the ideal frequency response and the other is the deviation on the interval from ω = 0 to ω = π. The deviation expression is the sum of weighted functions, where the general expression of these functions is equal to the half-sum of a pair of sinc sum functions plus π, and each weight is a window constant. Using the properties of the sinc sum function eight properties of the general expression and six properties of the deviation expression are deduced. By these properties both the relative errors of the passband and the change of their ripples can be small if each weight is proper and the truncated ideal differentiator is ideal at ω = 0. From the expression of the deviation a matrix equation with window constants as unknowns can be written. Examples are given about how to write the matrix equations and how to find the optimized window constants. Four new differentiator windows as a family are obtained. These windows belong to the fixed window. Different from existing windows, the new windows are optimized in terms of reducing the relative errors of the passband. Comparisons show that new windows are better or much better than the Hanning, Hamming, Blackman, Kaiser, Chebyshev and polynomial windows in terms of differentiator performances. © Springer Science+Business Media, LLC 2012. Source

Hua L.,Huaiyin Institute of Technology
International Journal of Digital Content Technology and its Applications | Year: 2012

Diffusion tensor imaging which measures the diffusion characteristics of water molecules in the brain, is an important technique for inferring the structure of the white matter tracts. However, DTI data is often underexploited in current techniques for segmentation and classification of these tracts. By incorporating not only scalar measures of diffusion such as fractional anisotropy, but also the diffusion directions, proximity to similarly oriented points, and a priori information about the location of major fiber bundles, this paper aims to develop more effective segmentation and classification algorithms. Source

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