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Fuzzy entropy design for non convex fuzzy set and application to mutual information 认领 引用 被引量：7
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作者 LEE Sang-Hyuk LEE Sang-Min +1 位作者 SOHN Gyo-Yong KIM Jaeh-Yung 《Journal of Central South University》 SCIE EI CAS 2011年第1期184-189,共6页
Fuzzy entropy was designed for non convex fuzzy membership function using well known Hamming distance measure.The proposed fuzzy entropy had the same structure as that of convex fuzzy membership case.Design procedure ... Fuzzy entropy was designed for non convex fuzzy membership function using well known Hamming distance measure.The proposed fuzzy entropy had the same structure as that of convex fuzzy membership case.Design procedure of fuzzy entropy was proposed by considering fuzzy membership through distance measure,and the obtained results contained more flexibility than the general fuzzy membership function.Furthermore,characteristic analyses for non convex function were also illustrated.Analyses on the mutual information were carried out through the proposed fuzzy entropy and similarity measure,which was also dual structure of fuzzy entropy.By the illustrative example,mutual information was discussed. 展开更多
关键词 fuzzy entropy non convex fuzzy membership function distance measure similarity measure mutual information
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k-NN Based Bypass Entropy and Mutual Information Estimation for Incremental Remote-Sensing Image Compressibility Evaluation 认领 引用 被引量：2
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作者 Xijia Liu Xiaoming Tao +1 位作者 Yiping Duan Ning Ge 《China Communications》 SCIE CSCD 2017年第8期54-62,共9页
Incremental image compression techniques using priori information are of significance to deal with the explosively increasing remote-sensing image data. However, the potential benefi ts of priori information are still... Incremental image compression techniques using priori information are of significance to deal with the explosively increasing remote-sensing image data. However, the potential benefi ts of priori information are still to be evaluated quantitatively for effi cient compression scheme designing. In this paper, we present a k-nearest neighbor(k-NN) based bypass image entropy estimation scheme, together with the corresponding mutual information estimation method. Firstly, we apply the k-NN entropy estimation theory to split image blocks, describing block-wise intra-frame spatial correlation while avoiding the curse of dimensionality. Secondly, we propose the corresponding mutual information estimator based on feature-based image calibration and straight-forward correlation enhancement. The estimator is designed to evaluate the compression performance gain of using priori information. Numerical results on natural and remote-sensing images show that the proposed scheme obtains an estimation accuracy gain by 10% compared with conventional image entropy estimators. Furthermore, experimental results demonstrate both the effectiveness of the proposed mutual information evaluation scheme, and the quantitative incremental compressibility by using the priori remote-sensing frames. 展开更多
关键词 remote-sensing incremental image compression entropy mutual information
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An uncertainty evaluation for storm surge risk analysis based on information utilization efficiency 认领 引用
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作者 Guilin LIU Siyu DING +3 位作者 Shichun SONG Bokai YANG Pengyu ZHU Liping WANG 《Journal of Oceanology and Limnology》 SCIE CAS CSCD 2026年第2期545-559,共15页
With the development of methods for predicting extreme hydrological elements using probabilistic approaches,several commonly used methods have emerged for analyzing the risk of storm surge disasters,including the Annu... With the development of methods for predicting extreme hydrological elements using probabilistic approaches,several commonly used methods have emerged for analyzing the risk of storm surge disasters,including the Annual Maxima method,the Peak-Over-Threshold method,the Gumbel distribution,and the Weibull distribution.Meanwhile,and emphases have been placed on assessing and comparing the applicability and stability of these various methods.To evaluate the rationality of different methods,we an entropy uncertainty analysis method was introduced based on information utilization efficiency,in which the sample Stochastic uncertainty is measured by the ratio of information entropy before and after sampling,i.e.,the information extraction efficiency of the sampling method.Additionally,the cognitive uncertainty of the research method is assessed by the ratio of mutual information between the model and the sample to the information entropy of the sample,i.e.,the information extraction efficiency of the mathematical model.Furthermore,we incorporated the group probability calculation method,information entropy and mutual information theory to analyze and calculate the entropy uncertainty more accurately.By applying this analysis to the design wave height and the recurrence period projected in the sea area west Guangdong of China,we believed that the most reasonable hazard assessment method shall be based on the over-threshold method combined with the Pareto distribution.Conversely,the assessment method based on the process extreme value method is deemed insufficiently reasonable and requires further research. 展开更多
关键词 uncertainty storm surge information entropy mutual information group probability calculation method
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Mutual Information and Relative Entropy of Sequential Effect Algebras 认领 引用 被引量：1
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作者 汪加梅 武俊德 Cho Minhyung 《Communications in Theoretical Physics》 SCIE CAS 2010年第8期215-218,共4页
In this paper,we introduce and investigate the mutual information and relative entropy on the sequentialeffect algebra,we also give a comparison of these mutual information and relative entropy with the classical ones... In this paper,we introduce and investigate the mutual information and relative entropy on the sequentialeffect algebra,we also give a comparison of these mutual information and relative entropy with the classical ones by thevenn diagrams.Finally,a nice example shows that the entropies of sequential effect algebra depend extremely on theorder of its sequential product. 展开更多
关键词 sequential effect algebra mutual information relative entropy
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基于Apriori与MIE联合分析虚劳相关中药成方制剂用药规律研究 认领 引用
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作者 李杨 马伟 《中国医药导报》 CAS 2026年第18期1-6,20,共6页
目的基于Apriori与MIE方法联合分析虚劳相关中药成方制剂用药规律。方法以“虚劳”“虚损”“劳倦”“乏力”等为关键词,检索《中华人民共和国药典》《药品标准·中药成方制剂》中相关成方制剂信息,并建立数据库。运用IBM SPSS Mode... 目的基于Apriori与MIE方法联合分析虚劳相关中药成方制剂用药规律。方法以“虚劳”“虚损”“劳倦”“乏力”等为关键词,检索《中华人民共和国药典》《药品标准·中药成方制剂》中相关成方制剂信息,并建立数据库。运用IBM SPSS Modeler 18.0软件中Apriori、互信息熵(MIE)算法和Cytoscape 3.9.1进行关联规则分析、MIE分析、频次分析等。同时,运用IBM SPSS Statistics 25.0,采用层次聚类法对高频药物进行聚类分析,分析用药规律。结果175种成方制剂中,涉及232味药材。黄芪、当归、茯苓等为治疗虚劳的核心高频药物;药性以温性为主,药味以甘味居多,归经侧重肾经与脾经;功效类别以补虚药为核心,兼顾活血化瘀、利水渗湿等。对使用次数≥20次的药物进行Apriori分析,获得40条强关联规则。MIE分析显示“白术-甘草”药对关联性最强(MIE=0.261)。聚类分析将方剂分为5类,分别适配气血两虚、肾阳虚衰等不同证型。结论通过Apriori与MIE分析,较为全面地揭示了现代成方制剂治疗虚劳的用药规律,研究结果为虚劳的规范化用药及新药研发提供数据支撑。 展开更多
关键词 中药成方制剂 虚劳 Apriori 互信息熵 用药规律
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Mutual information of cylinder pressure and combustion phase estimation in spark ignition engines 认领 引用
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作者 Huanyu DI Tielong SHEN 《Control Theory and Technology》 EI CSCD 2020年第1期34-42,共9页
For the study of internal combustion engines,combustion control is an important method to achieve high efficiency and low emissions.Currently,in-cylinder pressure sensor-based closed-loop control strategies have becom... For the study of internal combustion engines,combustion control is an important method to achieve high efficiency and low emissions.Currently,in-cylinder pressure sensor-based closed-loop control strategies have become the preferred solution.However,their productional application in automotive industries is limited due to the cost of intensive pressure acquisition for a whole cycle and the calculation load of combustion phase indicators.This paper proposes a method of combustion phase estimation for spark ignition(SI)engines.In this method,the combustion phase is estimated only based on pressure measurements at several crank angles.Information entropy and mutual information are introduced to analyze the feasibility and accuracy of the combustion phase estimation,which shows that the pressure measurements at selected points contain most of the information for the estimation.As a result,only pressure measurements at 3 points and ELM estimation models are required to obtain the combustion phase,instead of intensive data acquisition and calculation. 展开更多
关键词 Information entropy mutual information combustion phase estimation in-cylinder pressure extreme learning machine
Measuring causality by taking the directional symbolic mutual information approach 认领 引用
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作者 陈贵 谢磊 褚健 《Chinese Physics B》 SCIE EI CAS CSCD 2013年第3期556-560,共5页
We propose a novel measure to assess causality through the comparison of symbolic mutual information between the future of one random quantity and the past of the other.This provides a new perspective that is differen... We propose a novel measure to assess causality through the comparison of symbolic mutual information between the future of one random quantity and the past of the other.This provides a new perspective that is different from the conventional conceptions.Based on this point of view,a new causality index is derived that uses the definition of directional symbolic mutual information.This measure presents properties that are different from the time delayed mutual information since the symbolization captures the dynamic features of the analyzed time series.In addition to characterizing the direction and the amplitude of the information flow,it can also detect coupling delays.This method has the property of robustness,conceptual simplicity,and fast computational speed. 展开更多
关键词 causality measure Bandt and Pompe method mutual information transfer entropy
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Robust Image Registration Based on Mutual Information Measure 认领 引用 被引量：1
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作者 Witold Kosinski Pawel Michalak Piotr Gut 《Journal of Signal and Information Processing》 2012年第2期175-178,共4页
A new implementation of the image registration algorithm based on the mutual information is presented for the case of medical images. The registration is achieved if the maximum of the mutual information is attained. ... A new implementation of the image registration algorithm based on the mutual information is presented for the case of medical images. The registration is achieved if the maximum of the mutual information is attained. In this maximization process optimal values of five parameters of an affine transformation are searched. 展开更多
关键词 Image Registration Mutual Information Entropy Affine Transformation Medical Images
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基于互信息熵-改进PHD协同的非合作双基地雷达目标跟踪 认领 引用
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作者 潘嘉蒙 李纯 +2 位作者 郑曦楠 陈健 鲍庆龙 《雷达学报（中英文）》 EI CSCD 北大核心 2026年第2期637-649,共13页
针对非合作双基地雷达目标跟踪时主要面临的高杂波率、低检测概率等问题,该文提出了一种基于互信息熵和改进PHD滤波器的目标跟踪协同处理框架,首先将目标点和杂波点与参考模型间不同的统计相关程度量化为互信息熵值,基于互信息熵维特征... 针对非合作双基地雷达目标跟踪时主要面临的高杂波率、低检测概率等问题,该文提出了一种基于互信息熵和改进PHD滤波器的目标跟踪协同处理框架,首先将目标点和杂波点与参考模型间不同的统计相关程度量化为互信息熵值,基于互信息熵维特征完成杂波点迹筛除;其次通过动态权值补偿对经典PHD滤波器进行改进,减缓粒子权值归零过程的同时减少目标误删现象,解决低检测概率下点迹不连续且间隔随机给目标跟踪带来的点迹断联、目标丢失等问题。通过仿真实验验证了所提算法框架的有效性与性能,外场实测数据验证了所提方法在实际应用中可取得良好的目标跟踪结果。 展开更多
关键词 非合作双基地雷达 低检测概率 目标跟踪 互信息熵 PHD滤波
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面向高光谱遥感图像的MMRI-Boruta特征选择算法 认领 引用
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作者 张婧 孔霄 +2 位作者 曹峰 张超 李德玉 《郑州大学学报（理学版）》 CAS 北大核心 2026年第1期72-77,共6页
高光谱遥感图像特征选择旨在从高维光谱特征集中选择最优光谱特征子集,以消除冗余光谱特征来提高高光谱遥感图像分析的效率和精度。由此提出了一种混合型特征选择算法MMRI-Boruta,该算法首先对过滤式MRI特征选择算法进行改进,通过引入... 高光谱遥感图像特征选择旨在从高维光谱特征集中选择最优光谱特征子集,以消除冗余光谱特征来提高高光谱遥感图像分析的效率和精度。由此提出了一种混合型特征选择算法MMRI-Boruta,该算法首先对过滤式MRI特征选择算法进行改进,通过引入方差定义新的特征重要性评价指标,然后利用封装式的Boruta算法实现特征子集的进一步优化。所提算法结合了过滤式和封装式两种特征选择算法的优点,更易于获取最优特征子集。为了验证该算法的有效性,使用了两个经典的高光谱遥感图像数据集Indian Pines和Salinas对算法的性能进行了测试,实验结果表明该算法优于对比算法。 展开更多
关键词 高光谱遥感图像 特征选择 互信息 相关性 熵
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基于变量选择和二次分解的吸收塔出口SO2浓度预测 认领 引用 被引量：1
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作者 韦根原 郭腾飞 《华北电力大学学报（自然科学版）》 CAS 北大核心 2026年第3期147-158,共12页
为解决常规吸收塔出口SO2浓度预测模型对于输入变量选取不够合理、数据挖掘不充分的问题,提出了一种利用K近邻互信息变量选择算法(KNN-MI-VS)和变分模态分解-集合经验模态分解(VMD-EEMD)的二次分解技术建立吸收塔出口SO2浓度预测... 为解决常规吸收塔出口SO2浓度预测模型对于输入变量选取不够合理、数据挖掘不充分的问题,提出了一种利用K近邻互信息变量选择算法(KNN-MI-VS)和变分模态分解-集合经验模态分解(VMD-EEMD)的二次分解技术建立吸收塔出口SO2浓度预测模型的方法。通过K近邻互信息算法(KNN-MI)校正初始输入变量的时序迟延;利用KNN-MI-VS算法确定模型输入变量集合;采用VMD算法分解模型输入变量,之后利用EEMD算法分解样本熵值大的模态分量,然后保留两次分解结果中样本熵值小的模态分量作为预测模型输入;采用改进在线贯序极限学习机(IOS-ELM)网络建立预测模型。结果表明:基于KNN-MI-VS算法和VMD-EEMD二次分解的IOS-ELM预测模型相比于其他模型在变工况情况下具有更好的预测精度和适应能力。 展开更多
关键词 SO2浓度 预测 变分模态分解 集合经验模态分解 K近邻互信息 在线贯序极限学习机 样本熵
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基于声发射-特高频信号互信息熵的绝缘缺陷类型智能辨识方法 认领 引用
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作者 许广虎 何丹东 +1 位作者 冯煜轩 杜嘉宝 《无损检测》 CAS 2026年第7期88-93,共6页
由于气体绝缘设备/GIS腔体内具有多模态、非线性及强耦合特性,现有方法难以实现缺陷类型的精准诊断,故提出基于声发射-特高频信号互信息熵的绝缘缺陷类型智能辨识方法。同步采集绝缘缺陷产生的声发射信号与特高频信号,利用多分辨率广义... 由于气体绝缘设备/GIS腔体内具有多模态、非线性及强耦合特性,现有方法难以实现缺陷类型的精准诊断,故提出基于声发射-特高频信号互信息熵的绝缘缺陷类型智能辨识方法。同步采集绝缘缺陷产生的声发射信号与特高频信号,利用多分辨率广义S变换算法去除信号噪声,提取声发射信号与特高频信号之间的时间差。计算声发射信号与特高频信号的互信息熵,构建联合特征空间,通过改进粒子群优化算法筛选关键特征。将关键特征集合输入至混合模型中,其输出结果即为绝缘缺陷类型智能辨识结果。试验结果显示:所提方法的绝缘缺陷类型标签辨识准确率为99.78%,且在不同噪声环境下,缺陷类型误识率始终保持较低水平,最小值达到了0.3%,具有较强的抗噪能力。 展开更多
关键词 特高频信号 绝缘缺陷类型辨识 广义S变换 声发射信号 互信息熵理论 改进粒子群算法
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基于改进WOA-LSTM的时间序列流量预测方法 认领 引用
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作者 张智斌 褚红 《计算机仿真》 2026年第1期318-322,共5页
原始时间序列数据因其非平稳特性和高噪声水平,直接应用于预测模型往往会带来不准确的结果。为此,提出融合改进WOA-LSTM的时间序列流量预测新方法。利用互信息熵技术区分时间序列中的关键成分与噪声,并借助VMD算法对原始数据进行重构,... 原始时间序列数据因其非平稳特性和高噪声水平,直接应用于预测模型往往会带来不准确的结果。为此,提出融合改进WOA-LSTM的时间序列流量预测新方法。利用互信息熵技术区分时间序列中的关键成分与噪声,并借助VMD算法对原始数据进行重构,以降低其非平稳性和噪声干扰,改善数据质量。引入Tent混沌映射和自适应权重策略改进鲸鱼算法,增强算法的随机搜索能力和全局遍历性,避免了局部最优解的困扰,并可以动态调整搜索方向和步长,提升了收敛速度和优化性能。利用优化后的WOA算法调优LSTM网络的超参数,借助其自动学习能力,捕获时间序列中的复杂特征和长期依赖关系。通过与重构后的时间序列流量数据相适应,LSTM网络能够实现高精度的流量预测。实验结果表明,上述方法在时间序列流量预测方面表现优异,能够准确预测流量数据。 展开更多
关键词 互信息熵 时间序列 流量预测
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基于CNN-Mamba特征提取结合信息选择的红外与可见光图像融合方法 认领 引用
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作者 仵晓聪 冯鑫 +3 位作者 黄美娜 赵彬 胡开群 沈瑜 《光子学报》 EI CAS CSCD 北大核心 2026年第1期144-160,共17页
提出了一种基于CNN-Mamba特征提取结合信息选择的红外与可见光图像融合方法,旨在克服传统融合策略难以面对复杂场景和基于深度学习网络的融合策略复杂的问题。在图像编码阶段,引入了空间上下文感知模块(SCAM)来整合上下文特征信息并分... 提出了一种基于CNN-Mamba特征提取结合信息选择的红外与可见光图像融合方法,旨在克服传统融合策略难以面对复杂场景和基于深度学习网络的融合策略复杂的问题。在图像编码阶段,引入了空间上下文感知模块(SCAM)来整合上下文特征信息并分配注意力权重,接着设计了一种CNN结合Mamba网络的特征提取模块(CMFE)对两种模态图像信息进行深层次提取。在融合阶段,提出了全新的自适应权重选择融合层以保留更多源信息。通过消融实验结果可以看出本文提出的网络结构与损失函数具有合理性。在对比实验中,本文在MSRS、Road-Scene、TNO和M3FD四个公开数据集上将所提出的方法与七种先进融合方法进行对比,结果显示所提方法不仅具有更好的主观视觉效果,还具有最好的客观评价指标。最后为验证本文所提出方法的后续应用能力,针对Road-Scene数据集中的行人和车辆进行目标检测任务评估,结果表明本文方法在行人与车辆检测方面均取得最多的最优指标,这充分验证了本文所提出算法的综合性能。 展开更多
关键词 图像融合 归一化互信息 CMFE模块 信息熵 自适应权重选择融合层
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基于MIE-LSTM的短期光伏功率预测 认领 引用 被引量：56
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作者 吉锌格 李慧 +1 位作者 刘思嘉 王丽婕 《电力系统保护与控制》 EI CSCD 北大核心 2020年第7期50-57,共8页
提升精细化的光伏预测技术对电力系统的实时调度运行至关重要。它不仅依赖于预测模型的优劣,还依赖于训练样本日与预测日的相似程度。提出一种基于MIE-LSTM的短期光伏功率预测方法。在建立基于互信息熵(Mutual Information Entropy, MIE... 提升精细化的光伏预测技术对电力系统的实时调度运行至关重要。它不仅依赖于预测模型的优劣,还依赖于训练样本日与预测日的相似程度。提出一种基于MIE-LSTM的短期光伏功率预测方法。在建立基于互信息熵(Mutual Information Entropy, MIE)的相关性衡量指标基础上,计算出光伏功率与各气象因素间的互信息熵,从而对高维气象数据进行降维处理。然后,利用历史日与预测日多维气象因素间的加权互信息熵筛选出相似日样本。最后,通过长短期记忆(Long-short Term Memory, LSTM)神经网络预测模型训练并建立气象因素与光伏出力之间的映射关系。通过对某实测光伏电站不同天气类型下的发电功率进行预测分析,验证了新方法能够达到理想的预测精度。 展开更多
关键词 光伏功率预测 数值天气预报 互信息熵 相似日 长短期记忆神经网络
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Oil monitoring methods based on information theory 认领 引用
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作者 夏妍春 霍华 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2009年第3期396-401,共6页
To evaluate the wear condition of machines accurately,oil spectrographic entropy,mutual information and ICA analysis methods based on information theory are presented. A full-scale diagnosis utilizing all channels of ... To evaluate the wear condition of machines accurately,oil spectrographic entropy,mutual information and ICA analysis methods based on information theory are presented. A full-scale diagnosis utilizing all channels of spectrographic analysis can be obtained. By measuring the complexity and correlativity,the characteristics of wear condition of machines can be shown clearly. The diagnostic quality is improved. The analysis processes of these monitoring methods are given through the explanation of examples. The availability of these methods is validated and further research fields are demonstrated. 展开更多
关键词 entropy mutual information ICA oil monitoring wear
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Shannon information capacity of time reversal wideband multiple-input multiple-output system based on correlated statistical channels 认领 引用 被引量：3
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作者 杨瑜 王秉中 丁帅 《Chinese Physics B》 SCIE EI CAS CSCD 2016年第5期5-10,共6页
Utilizing channel reciprocity, time reversal（TR） technique increases the signal-to-noise ratio（SNR） at the receiver with very low transmitter complexity in complex multipath environment. Present research works abo... Utilizing channel reciprocity, time reversal（TR） technique increases the signal-to-noise ratio（SNR） at the receiver with very low transmitter complexity in complex multipath environment. Present research works about TR multiple-input multiple-output（MIMO） communication all focus on the system implementation and network building. The aim of this work is to analyze the influence of antenna coupling on the capacity of wideband TR MIMO system, which is a realistic question in designing a practical communication system. It turns out that antenna coupling stabilizes the capacity in a small variation range with statistical wideband channel response. Meanwhile, antenna coupling only causes a slight detriment to the channel capacity in a wideband TR MIMO system. Comparatively, uncorrelated stochastic channels without coupling exhibit a wider range of random capacity distribution which greatly depends on the statistical channel. The conclusions drawn from information difference entropy theory provide a guideline for designing better high-performance wideband TR MIMO communication systems. 展开更多
关键词 information entropy time reversal wideband multiple-input multiple-output（MIMO） system antenna mutual coupling
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Sentiment Lexicon Construction Based on Improved Left-Right Entropy Algorithm 认领 引用 被引量：1
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作者 YU Shoujian WANG Baoying LU Ting 《Journal of Donghua University(English Edition)》 CAS 2022年第1期65-71,共7页
A novel method of constructing sentiment lexicon of new words(SLNW)is proposed to realize effective Weibo sentiment analysis by integrating existing lexicons of sentiments,lexicons of degree,negation and network.Based... A novel method of constructing sentiment lexicon of new words(SLNW)is proposed to realize effective Weibo sentiment analysis by integrating existing lexicons of sentiments,lexicons of degree,negation and network.Based on left-right entropy and mutual information(MI)neologism discovery algorithms,this new algorithm divides N-gram to obtain strings dynamically instead of relying on fixed sliding window when using Trie as data structure.The sentiment-oriented point mutual information(SO-PMI)algorithm with Laplacian smoothing is used to distinguish sentiment tendency of new words found in the data set to form SLNW by putting new words to basic sentiment lexicon.Experiments show that the sentiment analysis based on SLNW performs better than others.Precision,recall and F-measure are improved in both topic and non-topic Weibo data sets. 展开更多
关键词 sentiment lexicon new word discovery left-right entropy sentiment analysis point mutual information(PMI)
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2020年版《中国药典》肝病相关中药成方制剂的MIE配伍网络分析 认领 引用 被引量：1
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作者 安晓玲 王顺刚 +5 位作者 秦琳 谭道鹏 鲁艳柳 何芋岐 张倩茹 杨艳 《中国实验方剂学杂志》 CAS CSCD 北大核心 2022年第2期199-207,共9页
目的:对功能主治与“肝病”相关的中药成方制剂进行药材配伍网络分析,揭示药材配伍规律。方法:以2020年版《中华人民共和国药典》(简称《中国药典》)(一部)为数据来源,以“肝”为检索词在中药成方制剂的功能主治项下进行检索。收集方剂... 目的:对功能主治与“肝病”相关的中药成方制剂进行药材配伍网络分析,揭示药材配伍规律。方法:以2020年版《中华人民共和国药典》(简称《中国药典》)(一部)为数据来源,以“肝”为检索词在中药成方制剂的功能主治项下进行检索。收集方剂信息,对药材、处方、功能主治相同但剂型不同的中药成方制剂进行合并,采用MIE方法对药材的方剂配伍关系进行量化打分,选择MIE值排名前25%的药对构建药材配伍网络。该网络以药材为网络节点,以药对的配伍关系为边。通过网络节点中心性分析发现重要药材、集群分析发现常用药材组合。随后,对药材集群相关方剂的主治疾病进行统计。采用Cytoscape 3.6.1对药材配伍网络进行可视化及拓扑结构分析。结果:2020年版《中国药典》(一部)共收录179个中药成方制剂,涉及428种药材。使用频数较高的药材有当归、白芍、甘草等,联系较强的药对有菟丝子-枸杞、陈皮-香附、墨旱莲-女贞子等。另外,每个网络集群药材对应不同的中药成方制剂及主治疾病,主要与消化疾病有关。结论:研究发现了中医临床治疗“肝病”的重要潜在药对以及常用药材组合,为揭示药材配伍规律提供理论参考,并为中药新药研究进行了方法学探索。 展开更多
关键词 《中华人民共和国药典》 肝病 中药成方制剂 MIE 配伍网络
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结合PCM和MIE的多模态图像配准方法 认领 引用 被引量：1
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作者 何彦杰 周焰 +1 位作者 刘超 曾剑新 《空军雷达学院学报》 2010年第5期372-375,共4页
针多模态图像配准问题,提出了一种基于相位一致性模型(PCM)和互信息熵(MIE)的配准方法.通过相位一致性模型同时提取多模态图像的角点和边缘特征,在边缘图上取角点的邻域,依据邻域间互信息熵的最小值在估计区域搜索匹配特征,利用RANSAC... 针多模态图像配准问题,提出了一种基于相位一致性模型(PCM)和互信息熵(MIE)的配准方法.通过相位一致性模型同时提取多模态图像的角点和边缘特征,在边缘图上取角点的邻域,依据邻域间互信息熵的最小值在估计区域搜索匹配特征,利用RANSAC算法去除错配,进而确定待配准图像间的变换参数.实验表明:该方法达到了像素级配准精度、求解稳定,对多模态引起的非线性灰度变化、光照变化、噪声等都具有较强的鲁棒性;计算精度较基于同类特征的配准方法高,角点、边缘等几何特征综合运用在多模态图像配准中效果良好. 展开更多
关键词 相位一致性 互信息熵 多模态 图像配准
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