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1.
测向误差的减小一直以来都是无线电测向精度提高的一个难点,对于不同的测向体制所采用的减小测向误差的方法都不尽相同。本文主要介绍的是相关干涉仪测向体制的基本原理以及通过内插法的应用来减小测向误差的方法。 相似文献
2.
Neutral Community Theory: How Stochasticity and Dispersal-Limitation Can Explain Species Coexistence
Neutral community theory explains biodiversity, i.e. the coexistence of several species, as the result of a stochastic balance
between immigration and extinction on a local level, and between speciation and extinction on a regional level. The most popular
model, presented by Hubbell in 2001, has seen many analytical developments in recent years, which can be used in model analysis,
model testing and model comparison. We review these developments here, and present alternative derivations and shine previously
unnoticed lights on them. 相似文献
3.
基于多站测向定位提供的目标辐射源方位角信息,提出了一种基于粒子滤波的测向定位跟踪算法.该算法采用序贯蒙特卡罗的粒子滤波技术,对目标辐射源方位信息进行粒子滤波融合处理,实现了对机动目标辐射源的无源定位跟踪.仿真实验表明,该算法适用于非线性模型和非高斯噪声的目标跟踪,与传统的基于卡尔曼滤波的多传感器融合跟踪算法相比,定位跟踪更为精确,从而对提高战场电子目标定位跟踪和精确打击具有广泛的应用价值. 相似文献
4.
Bamrung Tau Somchai 《AEUE-International Journal of Electronics and Communications》2006,60(4):279-289
This paper proposes a large-sample approximation of the maximum-likelihood estimator for direction finding in the presence of a spatially spread source. The key idea is to replace the parametric estimate of the four-dimensional nuisance parameter vector with the approximate one that depends on just one parameter of interest, called the nominal angle, thus permitting the use of one-dimensional optimization techniques. The proposed estimator is shown to be strongly consistent and asymptotically efficient, and the Cramér–Rao bound on its standard deviation is derived. Simulations show the estimator to outperform previously proposed estimators, such as the subspace-based estimator and others based on one-dimensional search. 相似文献
5.
With the rapid development of Internet technology, the innovative value and importance of the open source product community (OSPC) is becoming increasingly significant. Ensuring high robustness is essential to the stable development of OSPC with open characteristics. In robustness analysis, degree and betweenness are traditionally used to evaluate the importance of nodes. However, these two indexes are disabled to comprehensively evaluate the influential nodes in the community network. Furthermore, influential users have many followers. The effect of irrational following behavior on network robustness is also worth investigating. To solve these problems, we built a typical OSPC network using a complex network modeling method, analyzed its structural characteristics and proposed an improved method to identify influential nodes by integrating the network topology characteristics indexes. We then proposed a model containing a variety of relevant node loss strategies to simulate the changes in robustness of the OSPC network. The results showed that the proposed method can better distinguish the influential nodes in the network. Furthermore, the network’s robustness will be greatly damaged under the node loss strategies considering the influential node loss (i.e., structural hole node loss and opinion leader node loss), and the following effect can greatly change the network robustness. The results verified the feasibility and effectiveness of the proposed robustness analysis model and indexes. 相似文献
6.
Qi Nie Hao Jiang Si-Dong Zhong Qiang Wang Juan-Juan Wang Hao Wang Li-Hua Wu 《Entropy (Basel, Switzerland)》2022,24(7)
Community detection and structural hole spanner (the node bridging different communities) identification, revealing the mesoscopic and microscopic structural properties of complex networks, have drawn much attention in recent years. As the determinant of mesoscopic structure, communities and structural hole spanners discover the clustering and hierarchy of networks, which has a key impact on transmission phenomena such as epidemic transmission, information diffusion, etc. However, most existing studies address the two tasks independently, which ignores the structural correlation between mesoscale and microscale and suffers from high computational costs. In this article, we propose an algorithm for simultaneously detecting communities and structural hole spanners via hyperbolic embedding (SDHE). Specifically, we first embed networks into a hyperbolic plane, in which, the angular distribution of the nodes reveals community structures of the embedded network. Then, we analyze the critical gap to detect communities and the angular region where structural hole spanners may exist. Finally, we identify structural hole spanners via two-step connectivity. Experimental results on synthetic networks and real networks demonstrate the effectiveness of our proposed algorithm compared with several state-of-the-art methods. 相似文献
7.
Huan Qing 《Entropy (Basel, Switzerland)》2022,24(8)
In network analysis, developing a unified theoretical framework that can compare methods under different models is an interesting problem. This paper proposes a partial solution to this problem. We summarize the idea of using a separation condition for a standard network and sharp threshold of the Erdös–Rényi random graph to study consistent estimation, and compare theoretical error rates and requirements on the network sparsity of spectral methods under models that can degenerate to a stochastic block model as a four-step criterion SCSTC. Using SCSTC, we find some inconsistent phenomena on separation condition and sharp threshold in community detection. In particular, we find that the original theoretical results of the SPACL algorithm introduced to estimate network memberships under the mixed membership stochastic blockmodel are sub-optimal. To find the formation mechanism of inconsistencies, we re-establish the theoretical convergence rate of this algorithm by applying recent techniques on row-wise eigenvector deviation. The results are further extended to the degree-corrected mixed membership model. By comparison, our results enjoy smaller error rates, lesser dependence on the number of communities, weaker requirements on network sparsity, and so forth. The separation condition and sharp threshold obtained from our theoretical results match the classical results, so the usefulness of this criterion on studying consistent estimation is guaranteed. Numerical results for computer-generated networks support our finding that spectral methods considered in this paper achieve the threshold of separation condition. 相似文献
8.
Hailu Yang Qian Liu Jin Zhang Xiaoyu Ding Chen Chen Lili Wang 《Entropy (Basel, Switzerland)》2022,24(8)
The semantic social network is a complex system composed of nodes, links, and documents. Traditional semantic social network community detection algorithms only analyze network data from a single view, and there is no effective representation of semantic features at diverse levels of granularity. This paper proposes a multi-view integration method for community detection in semantic social network. We develop a data feature matrix based on node similarity and extract semantic features from the views of word frequency, keyword, and topic, respectively. To maximize the mutual information of each view, we use the robustness of L21-norm and F-norm to construct an adaptive loss function. On this foundation, we construct an optimization expression to generate the unified graph matrix and output the community structure with multiple views. Experiments on real social networks and benchmark datasets reveal that in semantic information analysis, multi-view is considerably better than single-view, and the performance of multi-view community detection outperforms traditional methods and multi-view clustering algorithms. 相似文献
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