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排序方式: 共有866条查询结果,搜索用时 15 毫秒
1.
Xu Shuiqing Chai Yi Hu Youqiang Huang Lei 《International Journal of Electronics》2018,105(6):1051-1062
Nonuniform sampling can be encountered in various practical processes because of random events or poor timebase. The analysis and applications of the nonuniform sampling for deterministic signals related to the linear canonical transform (LCT) have been well considered and researched, but up to now no papers have been published regarding the various nonuniform sampling theorems for random signals related to the LCT. The aim of this article is to explore the nonuniform sampling and reconstruction of random signals associated with the LCT. First, some special nonuniform sampling models are briefly introduced. Second, based on these models, some reconstruction theorems for random signals from various nonuniform samples associated with the LCT have been derived. Finally, the simulation results are made to prove the accuracy of the sampling theorems. In addition, the latent real practices of the nonuniform sampling for random signals have been also discussed. 相似文献
2.
Paravanparambil Rajakumar Jayachandran Sivasankaran Bijoy Nandan Mantodi Jima Odassery Krishnankutty Sreedevi Joseph Philomina Meethal Parambath Prabhakaran 《Lakes & Reservoirs: Research and Management》2019,24(4):372-390
A comprehensive study of the macrobenthic communities in the Kodungallur–Azhikode Estuary (KAE) was conducted during 2009–2011 period. A total of 18,846 organisms were collected, with 60% being malacostracans, followed by polychaetes (20%), molluscs (9%) and ‘others’ group (11%). A total of 79 species in 71 genera belonging to 49 families were identified, with 33 spp. being polychaetes, 26 spp. being malacostracans, 11 spp. being molluscs and 9 spp. being in the ‘others’ group. A single species of opportunistic amphipod (Americorophium triaeonyx) comprised more than 62.05% of the total numerical abundance of macrobenthos. The other dominant species were Obelia bidentata, Arcuatula senhousia, Cirolana fluviatilis, Prionospio cirrifera and Capitella sp. Canonical correspondence analysis (CCA) results indicated environmental parameters such as water column salinity, turbidity, sediment Eh, substratum type, chlorophyll‐a concentration, depth and organic matter in sediment were the significant factors influencing the distribution of macrobenthic species in the KAE. The present study provides baseline information for future KAE benthic studies. 相似文献
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为筛选稳定可靠的柳河大米产地确证元素,通过2次典范对应分析研究影响吉林省柳河大米采样点分布的环境因子,分析大米产地确证元素在区域尺度内的影响关系及其稳定性。典范对应分析结果表明,2个环境梯度轴分别解释大米矿物元素含量总方差的17.3%和23.4%,柳河大米矿物元素含量和环境变量之间存在较强的空间相关性,受产地环境变量影响最大的为Se元素,Ca、Zn、Mg含量受其影响最小,Mg、Ca、Na、Mn、Zn具有较好的稳定性和空间代表性,可作为柳河大米产地确证的指标元素。研究结果为建立柳河大米确证模型提供有效的理论依据。 相似文献
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AbstractThe aim of this study was to identify the latent structure and potential relationships between two sets of frictions measurements of warp-and-weft fabrics made with the sliding method and the Kawabata system (KES FB-4 method). First, linear relationships between all pairs of friction-related variables for the two methods were assessed and found to be weak and statistically not significant in most cases. Second, linear regression was applied to the variables previously exhibiting significant correlation only but the variables were found not to be useful for developing accurate predictive models. Third, multiple linear regression between a Kawabata variable and various parameters of the sliding method was used to construct a model that proved inaccurate owing to multicollinearity in the regressors; also, the method only allowed a single-dependent variable to be related. This was not the case with canonical correlation, which allowed two sets of variables to be correlated through multivariate analysis. This technique revealed a significant relationship between the two sets of friction-related variables. 相似文献
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根据Excel教学大纲的要求,总结出Excel考核的若干知识点,根据这些知识点提出了基于VBA技术的自动阅卷算法,并引入数据挖掘中的相异度与相似度作为单元格内容评分的度量,使得评分更加科学、合理。同时给出了一个Excel文档自动阅卷实例。 相似文献
8.
Chen Zhang Jieren Cheng Xiangyan Tang Victor S. Sheng Zhe Dong Junqi Li 《计算机、材料和连续体(英文)》2019,61(2):657-675
Distributed denial of service (DDoS) attacks launch more and more frequently and are more destructive. Feature representation as an important part of DDoS defense technology directly affects the efficiency of defense. Most DDoS feature extraction methods cannot fully utilize the information of the original data, resulting in the extracted features losing useful features. In this paper, a DDoS feature representation method based on deep belief network (DBN) is proposed. We quantify the original data by the size of the network flows, the distribution of IP addresses and ports, and the diversity of packet sizes of different protocols and train the DBN in an unsupervised manner by these quantified values. Two feedforward neural networks (FFNN) are initialized by the trained deep belief network, and one of the feedforward neural networks continues to be trained in a supervised manner. The canonical correlation analysis (CCA) method is used to fuse the features extracted by two feedforward neural networks per layer. Experiments show that compared with other methods, the proposed method can extract better features. 相似文献
9.
基于支持向量机和决策树的多分类方法存在错误累积问题,累积的错误往往使分类准确率下降,分类效果变差.在仔细分析了其产生错误累积原因的基础上,提出了基于哈夫曼树的支持向量机多分类方法.该方法首先将一个多分类问题分解为多个二分类问题,针对每个二分类问题使用支持向量机二分类方法解决;然后根据相异度来决策分类的优先顺序,构建基于哈夫曼树的支持向量机多分类模型;最后使用勒卡斯开源数据集进行验证,并将它与传统的支持向量机多分类方法进行实验比较.实验结果表明,新的方法在分类速度和分类精度上较传统的支持向量机多分类方法优越. 相似文献
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