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991.
研究了一类非平稳信号具有随机幅度的多项式相位信号的时延估计问题。充分利用信号的高阶循环平稳性,提出了一种基于信号高阶循环矩的时延估计方法。该方法容易实现,估计精度能有效地抑制加性平稳非高斯和任何高斯噪声。试验结果证明了提出方法的正确性。 相似文献
992.
993.
讨论一般随机分布的均值的区间估计问题,给出了一种求任意分布均值的置信区间的抽样方案:证明此抽样方案渐近有效,得出了关于任意分布均值的置信区间的新结果。 相似文献
994.
付晓萍 《成都电子机械高等专科学校学报》2009,12(2):82-84,89
针对从化森林资源保护与开发现状,深入分析从化森林资源保护与开发过程中出现的问题,提出相应的对策:以保护性开发为前提,科学规划,合理分区,有效开发利用森林资源;治理病虫害,改良不良林分;提高服务质量,完善配套设施;加大投资力度,开发深层次具有从化特色的旅游产品和旅游纪念品。 相似文献
995.
Álvaro E. Faria 《时间序列分析杂志》2011,32(6):607-617
Dynamic spatial Bayesian (DSB) models are proposed for the analytical modelling of radioactivity deposition after a nuclear accident. The proposed models are extensions of the multi‐variate time‐series dynamic linear models of West and Harrison (1997) to Markov random field processes. They combine the outputs from a long‐range atmospheric dispersal model with measured data (and prior information) to provide improved deposition prediction in space and time. Two versions of a Gaussian DSB model were applied to the radioactivity deposition in Bavaria over a 15 days period during the Chernobyl nuclear accident. One version had fixed functional forms for its spatial variances and covariances while the other allowed those to adapt and ‘learn’ from data in the conjugate Bayesian paradigm. There were two main sources of information for radioactivity deposition in our application: radioactivity measurements at a sparse set of 13 monitoring stations, and the numerical deposition evaluation of the atmospheric dispersal K‐model for the points of a 64 × 64 regular grid. We have analysed the temporal predictions (one‐step‐ahead forecasting) of those DSB models to show that the dispersal K‐model tended in general to underestimate the deposition levels at all times while the DSB models corrected for that although with different degrees of adjustment. 相似文献
996.
In this article, asymptotic theories for nonparametric methods are studied when they are applied to real‐time data. In particular, we derive central limit theorems for nonparametric density and regression estimators. For this we formally introduce a sequence of real‐time random variables indexed by a parameter related to fine gridding of time domain (or fine discretization). Our results show that the impact of fine gridding is greater in the density estimation case in the sense that strong dependence due to fine gridding severely affects the major strength of nonparametric density estimator (or its data‐adaptive property). In addition, we discuss some issues about nonparametric regression model with fine gridding of time domain. 相似文献
997.
Based on the powerful function of the hidden conditional random fields (HCRF) model in the expression and identification of semantic events and combining the webcast text information, a new framework for wonderful events automatic detection is put forward. Firstly, by analyzing and processing the webcast text, keyword combinations corresponding to each exciting event are obtained. Secondly, by classifying the webcast text to be detected, the happening time labels of each wonderful event are obtained. Thirdly, an HCRF model for semantic shot annotation is built to realize the semantic annotation of multiple types of semantic shots simultaneously, and the semantic shot sequence of the video clip is obtained. Finally, combining the multi-modal semantic clues, an HCRF model for the wonderful events detection and localization is effectively built in the case of small-scale training samples. Based on the mapping relationship among video low-level features, the multi-modal semantic clues and the wonderful semantic events, the inherent patterns of the wonderful events are excavated deeply in the multiple dimensions of the semantic structure, and then the wonderful events automatic detection, localization and segmentation are precisely achieved. Experiments show the effectiveness of this model. 相似文献
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1000.
《International Journal of Parallel, Emergent and Distributed Systems》2012,27(4):305-320
Given a set S of n proper circular arcs, it is required to identify a largest cardinality subset K[S] of S each two of whose members intersect. This paper describes an optimal parallel algorithm to compute K[S]. The algorithm is not based on any previously known sequential solution, and is designed for the CREW PRAM model of computation. It uses 0(n/logn) processors and runs in O(logn) time. An interesting feature of the algorithm is that it transforms the computational geometric problem at hand, to a problem involving computations on 0-1 matrices, and then transforms the latter back into a ray shooting problem in computational geometry. 相似文献