Shuffle operation on trajectories is useful in modeling parallel composition of words and languages. In this work, a new class of P systems with shuffle operation is presented. Such a system has language-objects and s...
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This paper addresses a robust H_(infinity) filtering problem for networked systems that are subject to both random transmission delays and packet dropouts. To start with, a data transmission model is established by em...
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This paper addresses a robust H_(infinity) filtering problem for networked systems that are subject to both random transmission delays and packet dropouts. To start with, a data transmission model is established by employing random series with Bernoulli distributions. A sufficient condition for robust stability with H_(infinity) constraints is derived for the filtering error system. The robust filter is designed in terms of the feasibility of a linear matrix inequality (LMI). The numerical examples are provided to show the effectiveness of the data transmission model and the proposed filtering method.
Randí et al. proposed a significant graphical representation for DNA sequences, which is very compact and avoids loss of information. In this paper, we build a fast algorithm for this graphical representation wit...
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DNA tile self-assembly is a promising paradigm for nanotechnology. Recently, many researches show that computation by DNA tile self-assembly maybe scalable. In this paper, we propose the algorithm for elliptic curve D...
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The maximum clique problem has diverse applications in the field of pattern recognition, computer vision, information processing etc. The connection between self-assembly and computation has implied that the tile asse...
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Membrane systems, also called P systems, are biologically inspired theoretical models of distributed and parallel computing. Tissue P system with cell separation is a computing model in the frame work of membrane comp...
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Randí;et al. proposed a famous spectral graphical representation of DNA sequences, and claimed that it avoids loss of information. In this paper we build two mathematical models for this graphical representation ...
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The aim of this study is to assess the functional connectivity from resting state functional magnetic resonance imaging (fMRI) data. Spectral clustering algorithm was applied to the realistic and real fMRI data acquir...
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ISBN:
(纸本)9781424466238
The aim of this study is to assess the functional connectivity from resting state functional magnetic resonance imaging (fMRI) data. Spectral clustering algorithm was applied to the realistic and real fMRI data acquired from a resting healthy subject to find functionally connected brain regions. In order to make computation of the spectral decompositions of the entire brain volume feasible, the similarity matrix has been sparsified with the t-nearestneighbor approach. Realistic data were created to investigate the performance of the proposed algorithm and comparing it to the recently proposed spectral clustering algorithm with the Nystrom approximation and also with some well-known algorithms such as the Cross Correlation Analysis (CCA) and the spatial Independent Component Analysis (sICA). To enhance the performance of the methods, a variety of data pre and post processing steps, including data normalization, outlier removal, dimensionality reduction by using wavelet coefficients, estimation of number of clusters and optimal number of independent components (ICs). Results demonstrate the applicability of the proposed algorithm for functional connectivity analysis.
For given graphs G1,G2, the 2-color Ramsey number R(G1,G2) is defined to be the least positive integer n such that every 2-coloring of the edges of complete graph Kn contains a copy of G1 colored with the first color ...
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For given graphs G1,G2, the 2-color Ramsey number R(G1,G2) is defined to be the least positive integer n such that every 2-coloring of the edges of complete graph Kn contains a copy of G1 colored with the first color or a copy of G2 colored with the second color. In this note, we obtained some new exact values of generalized Ramsey numbers such as cycle versus book, book versus book, complete bipartite graph versus complete bipartite graph.
The Ramsey multiplicity M(G) of a graph G is defined to be the smallest number of monochromatic copies of G in any two-coloring of edges of K R(G), where R(G) is the smallest integer n such that every graph on n verti...
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The Ramsey multiplicity M(G) of a graph G is defined to be the smallest number of monochromatic copies of G in any two-coloring of edges of K R(G), where R(G) is the smallest integer n such that every graph on n vertices either contains G or its complement contains G. With the help of computer algorithms, we obtain the exact values of Ramsey multiplicities for most of isolate-free graphs on five vertices, and establish upper bounds for a few others.
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