Granular computing which imitates the manner of human thinking is a mathematical tool to deal with incomplete, uncertain, imprecise and inconsistent knowledge. Just as a great umbrella, it may be regarded as a label o...
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ISBN:
(纸本)9781615677207
Granular computing which imitates the manner of human thinking is a mathematical tool to deal with incomplete, uncertain, imprecise and inconsistent knowledge. Just as a great umbrella, it may be regarded as a label of theories, methodologies, techniques and tools about granules, mainly including fuzzy set theory, rough set theory and quotient space theory. In this paper we discuss the relationship of three theories. Then we introduce a general model of granular computing and present a macrocosmic (microcosmic) hierarchical representation of granules.
We try to evaluate the sequential and non-sequential and flexible structural alignment methods on SCOP 1.71. Firstly, we compare the flexible method with rigid methods and compare the sequence order dependent methods ...
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We try to evaluate the sequential and non-sequential and flexible structural alignment methods on SCOP 1.71. Firstly, we compare the flexible method with rigid methods and compare the sequence order dependent methods with sequence order independent methods by two typical cases. Secondly, the performances of the above methods are evaluated using ten protein pairs which are considered as "hard to detect" similarities. Thirdly, we evaluate the methods by comparing the ROC curves based on their native score and geometric measure Qscore. Then we compare the methods directly using geometric match measure Qscore, which also allows the creation of a 'Best- of-All' method. The main conclusions are: (1) we find that the best alignments found by sequential methods are more consistent with the SCOP classification; (2) we show that ROC curves are of limited value and that their ranking of the methods is not consistent with the ranking implied by the quality of the alignments the methods find; (3) we also find that the alignments of flexible method and non-sequential methods are better than the corresponding alignments of rigid sequential method from the viewpoint of geometric superposition, and flexible method and non-sequential methods can find more cross-fold similarities.
Controller synthesis uses hardware description language and synthesis optimization tools from a higher abstract level. State transition graph of completely specified finite state machine is adopted to describe the beh...
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Controller synthesis uses hardware description language and synthesis optimization tools from a higher abstract level. State transition graph of completely specified finite state machine is adopted to describe the behavior of controller. State transition graph STG_org was generated before synthesized and state transition graph STG_ext was reversely extracted from structure realization of controller synthesis. If STG_org and STG_ext were equivalent then corresponding process of controller synthesis was correct. The paper gives a formal verification algorithm of controller synthesis with time complexity O(B 2 /Aldrt 1 (n)+A ldr t 2 (m,n)) .In order to further improve time complexity of algorithm, a verifying algorithm with synthetic information guidance was proposed. The algorithm is proved efficient in theory for its time complexity is decreased to O(Bldrt 1 (n) + Aldrt 2 (m,n)).
This paperpsilas purpose is to design a novel artificial immune model for network intrusion detection. This novel model can satisfy three main requirements of an efficient network intrusion detection system, namely, d...
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This paperpsilas purpose is to design a novel artificial immune model for network intrusion detection. This novel model can satisfy three main requirements of an efficient network intrusion detection system, namely, distributed, lightweight and self-organizing, can also quicken the process of affinity maturation of detector population and improve the efficiency of anomaly detection. The algorithms of adaptive extracting vaccines and vaccine operator are given in detail. And then, on the basis of Kimpsilas conceptual model for network intrusion detection, a novel artificial immune model and relevant algorithm for real-time network intrusion detection is proposed, which integrates vaccine operator with negative selection algorithm and clonal selection algorithm.
Using the locally conformal technique and the high-order symplectic integrators, the high- order conformal symplectic FDTD scheme is accurate and efficient for modeling the scattering from three-dimensional curved per...
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Using the locally conformal technique and the high-order symplectic integrators, the high- order conformal symplectic FDTD scheme is accurate and efficient for modeling the scattering from three-dimensional curved perfectly conducting objects. In addition, the decreased time step caused by the conformal model can be offset by using coarse grids.
While direct association rules are dedicated to describe the direct correlations among the items in a frequent itemset, indirect association rules are dedicated to describe the indirect correlations between the two it...
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While direct association rules are dedicated to describe the direct correlations among the items in a frequent itemset, indirect association rules are dedicated to describe the indirect correlations between the two items in a infrequent itemset. All the existing research works about indirect association rules are focused on improving the efficiency of mining algorithm for indirect association rules. Like incremental updating algorithm is important for mining association rules, incremental updating algorithm is also important for mining indirect association rules. In this paper, we put forward an incremental updating algorithm for mining indirect association rules to deal with the maintenance of discovered indirect association rules resulted from the change of the minimum support. The main idea is to re-utilize the results acquired in process with the old minimum support.
The traditional DCT-based real-valued discrete Gabor transform (RGDT) was limited to the critical sampling case. The biorthogonality relationship between the analysis window and the synthesis window for the transform ...
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The traditional DCT-based real-valued discrete Gabor transform (RGDT) was limited to the critical sampling case. The biorthogonality relationship between the analysis window and the synthesis window for the transform has not been unveiled. To overcome those drawbacks, this paper proposes a novel DCT-based real-valued discrete Gabor transform, which can be applied under both the critical sampling condition and the over-sampling condition. And the biorthogonality relationship between the analysis window and the synthesis window for the transform is also proved in this paper. Because it only involves real operations and can utilize fast DCT and DDCT algorithms for fast computation, it facilitates computation and implementation by hardware and/or software compared to the traditional complex-valued discrete Gabor transform.
The connections between Maxwell's equations and symplectic matrix are ***,we analyze the continuoustime Maxwell's difierentia I equationsInfree space and verify its time evolution matrix(TEMA)is symplectic-uni...
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The connections between Maxwell's equations and symplectic matrix are ***,we analyze the continuoustime Maxwell's difierentia I equationsInfree space and verify its time evolution matrix(TEMA)is symplectic-unitary matrix for complex space or symplectic-orthogonal matrix for real *** spatial differential operators are discrefized by pseudo-spectral(PS)approach with collocated grid and by finitedifrerenee(FD)method with staggered *** the PS approach,the TEMA conserves *** *** the FD method,the TEMA conserves symplectic-orthogonal *** integration scheme is usedInthe time *** particular,we find the symplectiness of the TEMA also can be *** mathematicaI proofs presented are helpful for deep researching the symplectic PSTD approach and the symplectic FDTD method.
The expectation-maximization (EM) algorithm is a popular approach for parameter estimation of finite mixture model (FMM). A drawback of this approach is that the number of components of the finite mixture model is not...
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ISBN:
(纸本)9781424423101
The expectation-maximization (EM) algorithm is a popular approach for parameter estimation of finite mixture model (FMM). A drawback of this approach is that the number of components of the finite mixture model is not known in advance, nevertheless, it is a key issue for EM algorithms. In this paper, a penalized minimum matching distance-guided EM algorithm is discussed. Under the framework of Greedy EM, a fast and accurate algorithm for estimating the number of components of the Gaussian mixture model (GMM) is proposed. The performance of this algorithm is validated via simulative experiments of univariate and bivariate Gaussian mixture models.
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