Most of the existing multi-source fusion methods are to choose the most reliable information from the multi-source information system to form a single-source information system. Obviously, this ...process is accompanied by information loss. In order to solve this problem, the multi-granulation method of information fusion in multi-source decision information system is studied in this paper. Firstly, decision support characteristic function and decision related characteristic function are constructed. Secondly, a pair of aggregation operators, including fixed aggregation operator and possible aggregation operator, is defined through two characteristic functions. Meanwhile, the two cases when thresholds α and β take special values are discussed. Finally, the relevant properties of aggregation operators in different situations are proposed and proved. What is more, two groups of comparative experiments are carried out to illustrate the effect of the aggregation operators. The experimental results show that the proposed multi-source fusion method can always find a set of thresholds (α,β), which makes the fusion effect better than the mean fusion.
The reducibility of C0(2) operators Zhu, Senhua; Yang, Yixin; Li, Ran ...
Journal of mathematical analysis and applications,
02/2020, Letnik:
482, Številka:
2
Journal Article
Recenzirano
In this paper, we give a necessary and sufficient condition for the reducibility of a C0(2) operator by using its characteristic function. Moreover, we obtain the number of reducing subspaces of a ...C0(2) operator. As an application, we will restudy the reducibility of the truncated Toeplitz operator Az2.
The cosine willow tree method (Ma et al., 2021) provides a first lattice framework to price options and calculate risk measures under various Lévy process models. However, it may fail under some ...circumstances due to the failure in moment matching by the Johnson curve. In this paper, we propose a more robust approach to construct a willow tree via numerical integration. Since the moment matching by the Johnson curve is avoided, the new approach provides a better convergence than the cosine willow tree method. Finally, numerical experiments are carried out to support our claims.
In this article, we prove two results on the value distribution of meromorphic functions. Using the theorem of Yamanoi, the first result gives a precise estimation of the relationship between the ...characteristic function of a meromorphic function and its
th derivative in a concise form. This result extends and improves some results of Shan, Singh, Gopalakrishna, Edrei, Weitsman, Yang, Wu and Wu, etc. The second result answers a conjecture posed by C. C. Yang. This conjecture turned to be false by a counter-example, but it will be true with an additional condition.
Assessing structural reliability problem with high-dimensional random inputs is still challenging due to the “curse of dimensionality”. In this paper, this challenge is addressed by extending the ...Generalized Distribution Reconstruction Method via Characteristic Function Inversion (GDRM-CFI). Specifically, a clustering-based partially stratified sampling method is proposed for selecting high-dimensional points to numerically evaluate the characteristic function (CF) curve of complex high-dimensional problems. An improved number-theoretical method (i-NTM) is used to establish a uniform, efficient point set, ensuring determinism and reducing variability. Subsequently, a partial stratification approach partitions the high-dimensional space into orthogonal two-dimensional subspaces. The fundamental point set is projected into each subspace, and the k-means clustering algorithm identifies centroids within each, acting as representative points. The complete set of representative points from all subspaces formulates the high-dimensional point set. Numerical examples are investigated, which demonstrate the proposed method is effective for high-dimensional structural reliability assessment.
•The proposed method can generate high-dimensional samples with great uniformity.•The proposed method is applicable to high-dimensional reliability assessment.•The proposed method outperforms some widely-used high-dimensional sampling methods.•Numerical examples validate the effectiveness of the proposed method.
Inverse spectral problem for a self-adjoint differential operator, which is the sum of the operator of the third derivative on a finite interval and of the operator of multiplication by a real ...function (potential), is solved. Closed system of integral linear equations is obtained. Via solution to this system, the potential is calculated. It is shown that the main parameters of the obtained system of equations are expressed via spectral data of the initial operator. It is established that the potential is unambiguously defined by the four spectra.
This note presents a simple proof of the characteristic function of Student's t-distribution. The method of proof, which involves finding a differential equation satisfied by the characteristic ...function, is applicable to many other distributions.
Tests of fit for classes of distributions that include the Weibull, the Pareto and the Fréchet families are proposed. The new tests employ the novel tool of the min–characteristic function and are ...based on an L2–type weighted distance between this function and its empirical counterpart applied on suitably standardized data. If data–standardization is performed using the MLE of the distributional parameters then the method reduces to testing for the standard member of the family, with parameter values known and set equal to one. Asymptotic properties of the tests are investigated. A Monte Carlo study is presented that includes the new procedure as well as competitors for the purpose of specification testing with three extreme value distributions. The new tests are also applied on a few real–data sets.
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