• Title/Summary/Keyword: entropy theory

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A New $H_2$ Bound for $H_{\infty}$ Entropy

  • Zhang, Hui;Sun, Youxian
    • International Journal of Control, Automation, and Systems
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    • v.6 no.4
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    • pp.620-625
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    • 2008
  • The $H_{\infty}$ entropy in $H_{\infty}$ control theory is discussed based on investigating information transmission in continuous-time linear stochastic systems. It is proved that the stabilizing feedback does not change the time-average information transmission between system input and output, and the $H_{\infty}$ entropies of open- and closed-loop stable transfer functions are bounded by mutual information rate between input and output in the open-loop system. Furthermore, a new $H_2$ upper bound for $H_{\infty}$ entropy is introduced with a numerical example. Thus the $H_{\infty}$ entropy of a stable transfer function is sandwiched between $H_2$ norms of the original system and a static feedback system.

Computing Semantic Similarity between ECG-Information Concepts Based on an Entropy-Weighted Concept Lattice

  • Wang, Kai;Yang, Shu
    • Journal of Information Processing Systems
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    • v.16 no.1
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    • pp.184-200
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    • 2020
  • Similarity searching is a basic issue in information processing because of the large size of formal contexts and their complicated derivation operators. Recently, some researchers have focused on knowledge reduction methods by using granular computing. In this process, suitable information granules are vital to characterizing the quantities of attributes and objects. To address this problem, a novel approach to obtain an entropy-weighted concept lattice with inclusion degree and similarity distance (ECLisd) has been proposed. The approach aims to compute the combined weights by merging the inclusion degree and entropy degree between two concepts. In addition, another method is utilized to measure the hierarchical distance by considering the different degrees of importance of each attribute. Finally, the rationality of the ECLisd is validated via a comparative analysis.

Estimation for the Variation of the Concentration of Greenhouse Gases with Modified Shannon Entropy (변형된 샤논 엔트로피식을 이용한 온실가스 농도변화량 예측)

  • Kim, Sang-Mok;Lee, Do-Haeng;Choi, Eol;Koh, Mi-Sol;Yang, Jae-Kyu
    • Journal of Environmental Science International
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    • v.22 no.11
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    • pp.1473-1479
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    • 2013
  • Entropy is a measure of disorder or uncertainty. This terminology is qualitatively used in the understanding of its correlation to pollution in the environmental area. In this research, three different entropies were defined and characterized in order to quantify the qualitative entropy previously used in the environmental science. We are dealing with newly defined distinct entropies $E_1$, $E_2$, and $E_3$ originated from Shannon entropy in the information theory, reflecting concentration of three major green house gases $CO_2$, $N_2O$ and $CH_4$ represented as the probability variables. First, $E_1$ is to evaluate the total amount of entropy from concentration difference of each green house gas with respect to three periods, due to industrial revolution, post-industrial revolution, and information revolution, respectively. Next, $E_2$ is to evaluate the entropy reflecting the increasing of the logarithm base along with the accumulated time unit. Lastly, $E_3$ is to evaluate the entropy with a fixed logarithm base by 2 depending on the time. Analytical results are as follows. $E_1$ shows the degree of prediction reliability with respect to variation of green house gases. As $E_1$ increased, the concentration variation becomes stabilized, so that it follows from linear correlation. $E_2$ is a valid indicator for the mutual comparison of those green house gases. Although $E_3$ locally varies within specific periods, it eventually follows a logarithmic curve like a similar pattern observed in thermodynamic entropy.

Moving Object Detection using Clausius Entropy and Adaptive Gaussian Mixture Model (클라우지우스 엔트로피와 적응적 가우시안 혼합 모델을 이용한 움직임 객체 검출)

  • Park, Jong-Hyun;Lee, Gee-Sang;Toan, Nguyen Dinh;Cho, Wan-Hyun;Park, Soon-Young
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.47 no.1
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    • pp.22-29
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    • 2010
  • A real-time detection and tracking of moving objects in video sequences is very important for smart surveillance systems. In this paper, we propose a novel algorithm for the detection of moving objects that is the entropy-based adaptive Gaussian mixture model (AGMM). First, the increment of entropy generally means the increment of complexity, and objects in unstable conditions cause higher entropy variations. Hence, if we apply these properties to the motion segmentation, pixels with large changes in entropy in moments have a higher chance in belonging to moving objects. Therefore, we apply the Clausius entropy theory to convert the pixel value in an image domain into the amount of energy change in an entropy domain. Second, we use an adaptive background subtraction method to detect moving objects. This models entropy variations from backgrounds as a mixture of Gaussians. Experiment results demonstrate that our method can detect motion object effectively and reliably.

The annual variation pattern and regional division of weather eatropy in South Korea (남한의 일기엔트로피의 연변화유형과 지역구분)

  • ;Park, Hyun-Wook
    • Journal of the Korean Geographical Society
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    • v.30 no.3
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    • pp.207-229
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    • 1995
  • The characteristics of weather and climate in South Korea has great influences on the annual variation pattern and the appearance of the prevailing weather. The purpose of this paper is to induce the quantity of the weather entropy and annual variation pattern using the information theory and the principal component analysis. And author tried to classify the region according to the variation of its space scale, The raw materials used for this study are the daily cloudiness and precipitation during the years 1990-1994 at 69 stations in South Korea. It is divided into four classes of fine, clear, cloudy and rainy. The rcsults of this study can be summarized as follows: 1. Thc characteristics of annual variation pattern of weather entropy can be chiefly divided into five categories and the accumulated contributory rate of these is 73.1%. 2. Annual variation pattern of the first principal component reaches smaller in May, April and September than national average, and becomes greater when the winter comes. This weather entropy's quantity(Rs1) is positive in most area to the western sife of Soback Mountains and negative in most seaside area to the eastern side of Soback Mountains. 3. The characteristics of annual variation pattern of the second principal component shows that the entropy is more smaller in summer than national average and the rest of seasons shows larger, especially in January, May and September. This weather entropy's quantity(Rs2) is positive in most Honam Inland area to the western side of Soback Mountains and negative in most Youngnam Inland area to the eastern side of Soback Mountains. 4. Eight type regions (S1-S11) are classified based on the occurrences of minimum weather entropy in South Korea, and annual variation pattern of weather entropy by principal component analysis may be classified into sixteen type regions (Rs1-Rs9). Putting these things together, South Korea can be classifieed into thirty one type regions (Rs1S7-Rs9S10).

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Performance Enhancing Technique for Terrain Referenced Navigation Systems using Terrain Roughness and Information Gain Based on Information Theory (정보이론기반 지형 험준도 및 정보이득을 이용한 지형대조항법 성능 향상 기법)

  • Nam, Seongho
    • Journal of the Korea Institute of Military Science and Technology
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    • v.20 no.3
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    • pp.307-314
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    • 2017
  • Terrain referenced navigation(TRN) system is an attractive method for obtaining position based on terrain measurements and a terrain map. We focus on TRN systems based on the point mass filter(PMF) which is one of the recursive Bayesian method. In this paper, we propose two kinds of performance index for Bayesian filter. The proposed indices are based on entropy and mutual information from information theory. The first index measures roughness of terrain based on entropy of likelihood. The second index named by information gain, which is the mutual information between priori and posteriori distribution, is a quantity of information gained by updating measurement at each step. The proposed two indices are used to determine whether the solution from TRN is adequate for TRN/INS integration or not, and this scheme gives the performance improvement. Simulation result shows that the proposed indices are meaningful and the proposed algorithm performs better than normal TRN algorithm.

Grouting effects evaluation of water-rich faults and its engineering application in Qingdao Jiaozhou Bay Subsea Tunnel, China

  • Zhang, Jian;Li, Shucai;Li, Liping;Zhang, Qianqing;Xu, Zhenhao;Wu, Jing;He, Peng
    • Geomechanics and Engineering
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    • v.12 no.1
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    • pp.35-52
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    • 2017
  • In order to evaluate the grouting effects of water-rich fault in tunnels systematically, a feasible and scientific method is introduced based on the extension theory. First, eight main influencing factors are chosen as evaluation indexes by analyzing the changes of permeability, mechanical properties and deformation of surrounding rocks. The model of evaluating grouting effects based on the extension theory is established following this. According to four quality grades of grouting effects, normalization of evaluation indexes is carried out, aiming to meet the requirement of extension theory on data format. The index weight is allocated by adopting the entropy method. Finally, the model is applied to the grouting effects evaluation in water-rich fault F4-4 of Qingdao Jiaozhou Bay Subsea Tunnel, China. The evaluation results are in good agreement with the test results on the site, which shows that the evaluation model is feasible in this field, providing a powerful tool for systematically evaluating the grouting effects of water-rich fault in tunnels.

New Information Behavior Model: Life Paradigm Based (생명 패러다임 정보행태모델)

  • Lee, Hyuk-Jin
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.27 no.1
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    • pp.217-235
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    • 2016
  • Humanities academia and scientific community have been fused together in 21st centurty and it creates new theories and models. Among them, the embodied cognition theory has received attention in several related fields. This study reviews the major metatheories in information user behavior with their limitations. Then, "Life paradigm information behavior model" is suggested as a new theory, which communsurates with new era's request, introducing the embodied cognition theory and the entropy concept. By overcoming the limitations of individual approach to the information retrieval and user behaviors, we expect the discourse of the new integrated information retrieval paradigm.

The Slip-Wall Boundary Conditions Effects and the Entropy Characteristics of the Multi-Species GH Solver (다화학종 GH 방정식의 정확성 향상을 위한 벽면 경계조건 연구 및 GH 방정식의 엔트로피 특성 고찰)

  • Ahn, Jae-Wan;Kim, Chong-Am
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.37 no.10
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    • pp.947-954
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    • 2009
  • Starting from the Eu's GH(Generalized Hydrodynamic) theory, the multi-species GH numerical solver is developed in this research and its computatyional behaviors are examined for the hypersonic rarefied flow over an axisymmetric body. To improve the accuracy of the developed multi-species GH solver, various slip-wall boundary conditions are tested and the computed results are compared. Additionally, in order to validate the entropy characteristics of the GH equation, the entropy production and entropy generation rates of the GH equation are investigated in the 1-dimensional normal shock structure test at a high Knudsen number.

A New Formulation of the Reconstruction Problem in Neutronics Nodal Methods Based on Maximum Entropy Principle (노달방법의 중성자속 분포 재생 문제에의 최대 엔트로피 원리에 의한 새로운 접근)

  • Na, Won-Joon;Cho, Nam-Zin
    • Nuclear Engineering and Technology
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    • v.21 no.3
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    • pp.193-204
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    • 1989
  • This paper develops a new method for reconstructing neutron flux distribution, that is based on the maximum entropy Principle in information theory. The Probability distribution that maximizes the entropy Provides the most unbiased objective Probability distribution within the known partial information. The partial information are the assembly volume-averaged neutron flux, the surface-averaged neutron fluxes and the surface-averaged neutron currents, that are the results of the nodal calculation. The flux distribution on the boundary of a fuel assembly, which is the boundary condition for the neutron diffusion equation, is transformed into the probability distribution in the entropy expression. The most objective boundary flux distribution is deduced using the results of the nodal calculation by the maximum entropy method. This boundary flux distribution is then used as the boundary condition in a procedure of the imbedded heterogeneous assembly calculation to provide detailed flux distribution. The results of the new method applied to several PWR benchmark problem assemblies show that the reconstruction errors are comparable with those of the form function methods in inner region of the assembly while they are relatively large near the boundary of the assembly. The incorporation of the surface-averaged neutron currents in the constraint information (that is not done in the present study) should provide better results.

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