• Journal of Digital Contents Society
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• v.9 no.2
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• pp.357-362
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• 2008

The new approach was proposed which uses Shannon function based on variable length in order to detect the edges of image. The proposed casted the detection of edges in images on the space information of the images. In addition the algorithm which measures the possibility of edges was proposed. Lots of simulations showed that the approach in this paper was more good than the conventional methods in detecting meaningful discontinuities in gray level.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.109-112
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• 2001

영상분할에 있어서 최적의 임계치를 구하는 것은 영상을 구성하고 있는 픽셀들을 의미있는 집단으로 나누는 거와 같으며 이를 위하여 퍼지화 정도를 측정하여 최소의 퍼지화 정도를 갖는 임계치를 최적의 임계치로 설정한다. 일반적으로 소속도는 하나의 픽셀과 그 픽셀이 속한 영역의 관계로 표현될 수 있는데 소속도 계산을 위한 엔트로피로 샤논(Shannon)함수를 사용한다[1]. Liang-Kai Huang에 의하여 제안된 알고리즘은 그 수렴속도 면에 있어서 많은 문제점을 갖고 있다[2]. 본 논문에서는 이런 수렴속도를 좀더 개선하기 위하여 SPOI(Simplified Fixed Point Iteration)를 제안하고 여러 가지 실험영상을 사용하여 졔안된 논문의 우수성을 보이고자 한다. 실험결과 적절한 임계치를 구하면서도 기존의 논문보다 속도면에서 상당히 우수한 특성을 보이고 있다.

• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.5-8
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• 2000

In this paper, we propose new algorithms for the partition of input space and the generation of fuzzy control rules. The one consists of Shannon and extended fuzzy entropy function, the other consists of adaptive fuzzy neural system with back propagation teaming rule. The focus of this scheme is to realize the optimal fuzzy rule base with the minimal number of the parameters of the rules, reducing the complexity of the system. The proposed algorithm is tested with the time series prediction problem using Mackey-Glass chaotic time series.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.83-93
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• 2013

By comparing Wiener's MMSE on stochastic signal transmission with Shannon's mutual information first proved by C.E. Shannon in terms of information theory, connections between two approaches were investigated. What Wiener wanted to see in signal transmission in noisy channel is to try to capture fundamental limits for signal quality in signal estimation. On the other hands, Shannon was interested in finding fundamental limits of signal quantity that maximize the uncertainty in mutual information using the entropy concept in noisy channel. First concern of this paper is to show that in deriving limits of Shannon's point to point fundamental channel capacity, Shannon's mutual information obtained by exploiting MMSE combiner and Wiener filter's MMSE are interelated by integro-differential equantion. Then, At the meeting point of Wiener's MMSE and Shannon's mutual information the upper bound of spectral efficiency and the lower bound of energy efficiency were computed. Choosing a proper lattice-type code of a mod-${\Lambda}$AWGN channel model and MMSE estimation of ${\alpha}$ confirmed to lead to the fundamental Shannon capacity limits.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.5
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• pp.1047-1054
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• 2012

Atrial fibrillation (AF) is the most common arrhythmia encountered in clinical practice, and its risk increases with age. Conventionally, the way of detecting AF was the time·frequency domain analysis of RR variability. However, the detection of ECG signal is difficult because of the low amplitude of the P wave and the corruption by the noise. Also, the time·frequency domain analysis of RR variability has disadvantage to get the details of irregular RR interval rhythm. In this study, we describe an atrial fibrillation pattern analysis based on symbolization and information entropy. We transformed RR interval data into symbolic sequence through differential partition, analyzed RR interval pattern, quantified the complexity through Shannon entropy and detected atrial fibrillation. The detection algorithm was tested using the threshold between 10ms and 100ms on two databases, namely the MIT-BIH Atrial Fibrillation Database.

• Journal of Environmental Policy
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• v.7 no.3
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• pp.41-61
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• 2008

Although the size of the organic food market in Korea has increased significantly, its further development is hampered by the information asymmetry between the producers and consumers of organic food. It isn't just about revitalizing the market; it's also about Korean farmers surviving an era of trade liberalization. In order to produce more value-added products, the information asymmetry issue has to be resolved regarding the organic food market and other agricultural credence goods such as Han-woo(Korean beef). Therefore, measuring information asymmetry has become a central issue. One way to measure asymmetry is to use Game Theory. However, in practice, estimating payoffs at the industry level is hard to accomplish, and even when it is possible, the reliability of the estimated payoffs is not guaranteed. As an alternative, the concept of Information Entropy(disorder level of information), developed by Shannon(1948), was used in this study. It is proposed that this measure should be used when assessing the level of information asymmetry in the Korean organic food market. Using recent data, it was found that information entropy in the Korean organic food market has been decreasing constantly since 2003. Therefore, it was proposed that measures should be adopted by the government to improve the certification system of organic food.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.3
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• pp.87-96
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• 2014

Hackers try to achieve their purpose in a variety of ways, such as operating own website and hacking a website. Hackers seize a large amount of private information after they have made a zombie PC by using malicious code to upload the website and it would be used another hacking. Almost detection technique is the use Snort rule. When unknown code and the patterns in IDS/IPS devices are matching on network, it detects unknown code as malicious code. However, if unknown code is not matching, unknown code would be normal and it would attack system. Hackers try to find patterns and make shellcode to avoid patterns. So, new method is needed to detect that kinds of shellcode. In this paper, we proposed a noble method to detect the shellcode by using Shannon's information entropy.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.1
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• pp.61-73
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• 2012

The paper presents the novel approach to solve some problems occurred in application of the genetic algorithm to the determination of the optimal tire pattern sequence in order to reduce the tire air-pumping noise which is generated by the repeated compression and expansion of the air cavity between tire pattern and road surface. The genetic algorithm has been used to find the optimal tire pattern sequence having a low level of tire air-pumping noise using the image based air-pumping model. In the genetic algorithm used in the previous researches, there are some problems in the encoding structure and the selection of objective function. The paper proposed single encoding element with five integers, divergent objective function based on evolutionary process and the optimal evolutionary rate based on Shannon entropy to solve the problems. The results of the proposed genetic algorithm with evolutionary process are compared with those of the randomized algorithm without evolutionary process on the two-dimensional normal distribution. It is confirmed that the genetic algorithm is more effective to reduce the peak value of the predicted tire air-pumping noise and the consistency and cohesion of the obtained simulation results are also improved in terms of probability.

• 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.

• Journal of Korea Multimedia Society
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• v.3 no.2
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• pp.201-208
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• 2000

In this paper We describe an algorithm which is devised for 4he partition o# the input space and the generation of fuzzy rules by the fuzzy entropy and tested with the time series prediction problem using Mackey-Glass chaotic time series. This method divides the input space into several fuzzy regions and assigns a degree of each of the generated rules for the partitioned subspaces from the given data using the Shannon function and fuzzy entropy function generating the optimal knowledge base without the irrelevant rules. In this scheme the basic idea of the fuzzy neural network is to realize the fuzzy rules base and the process of reasoning by neural network and to make the corresponding parameters of the fuzzy control rules be adapted by the steepest descent algorithm. The Proposed algorithm has been naturally derived by means of the synergistic combination of the approximative approach and the descriptive approach. Each output of the rule's consequences has expressed with its connection weights in order to minimize the system parameters and reduce its complexities.