• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.3
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• pp.50-59
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• 2011

In this paper, we present a spectrum sensing method by exploiting the relationship of previous and current detected data sets in frequency domain. Most of the traditional spectrum sensing methods only consider the current detected data sets of Primary User (PU). Previous state of PU is a kind of conditional probability that strengthens the reliability of the detector. By considering the relationship of the previous and current spectrum sensing, cross entropy-based spectrum sensing is proposed to detect PU signal more effectively, which has a strengthened performance and is robust. When previous detected signal is noise, the discriminating ability of cross entropy-based spectrum sensing is no better than conventional entropy-based spectrum sensing. To address this problem, we propose an improved cross entropy-based frequency-domain spectrum sensing. Regarding the spectrum sensing scheme, we have derived that the proposed method is superior to the cross entropy-based spectrum sensing. We proceed a comparison of the proposed method with the up-to-date entropy-based spectrum sensing in frequency-domain. The simulation results demonstrate the performance improvement of the proposed spectrum sensing method.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.2
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• pp.121-128
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• 2008

Accurate voice activity detection have a great impact on performance of speech applications including speech recognition, speech coding, and speech communication. In this paper, we propose methods for voice activity detection that can adapt to various car noise situations during driving. Existing voice activity detection used various method such as time energy, frequency energy, zero crossing rate, and spectral entropy that have a weak point of rapid. decline performance in noisy environments. In this paper, the approach is based on existing spectral entropy for VAD that we propose voice activity detection method using MFB(Met-frequency filter banks) spectral entropy, gradient FFT(Fast Fourier Transform) spectral entropy. and gradient MFB spectral entropy. FFT multiplied by Mel-scale is MFB and Mel-scale is non linear scale when human sound perception reflects characteristic of speech. Proposed MFB spectral entropy method clearly improve the ability to discriminate between speech and non-speech for various in noisy car environments that achieves 93.21% accuracy as a result of experiments. Compared to the spectral entropy method, the proposed voice activity detection gives an average improvement in the correct detection rate of more than 3.2%.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.347-352
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• 2011

Entropy used for measuring the richness in details of the image and absolute mean brightness error(AMBE) providing a change in the image global appearance are two quantitative measures generally used for measuring quality of images. In this paper, we propose an entropy and AMBE-based thresholding method to binalize a given image. The effectiveness of the proposed method is demonstrated by thresholding experiments on nine test images and comparison with other conventional thresholding methods, that is, Otsu method and entropy-based method.

• Journal of the Korean Data and Information Science Society
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• v.16 no.3
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• pp.705-712
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• 2005

Entropy is the basic concept of information theory. It is well defined for random varibles with known probability density function(pdf). For given data with unknown pdf, entropy should be estimated. Usually, estimation of entropy is based on the approximations. In this paper, we consider a kernel based approximation and compare it to the cumulant approximation method for several distributions. Monte carlo simulation for various sample size is conducted.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.543-548
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• 2011

Entropy measuring the richness in details of the image is generally obtained by using the histogram of gray levels in an image, and has been widely used as an index for thresholding of the image. In this paper, we propose an entropy-based thresholding method, where the entropy is obtained not by the histogram but by the variance of the gray levels, to binalize a given image. The effectiveness of the proposed method is demonstrated by thresholding experiments on nine test images and comparison with conventional two thresholding methods, that is, Otsu method and entropy-based method using the histogram.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.837-847
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• 2012

Inverse Gaussian distribution is widely used in applications to analyze and model right-skewed data. To assess the appropriateness of the distribution prior to data analysis, Mudholkar and Tian (2002) proposed an entropy-based test of fit. The test is based on the entropy power fraction(EPF) index suggested by Gokhale (1983). The simulation results report that the power of the entropy-based test is superior compared to other goodness-of-fit tests; however, this observation is based on the small-scale simulation results on the standard exponential, Weibull W(1; 2) and lognormal LN(0:5; 1) distributions. A large-scale simulation should be performed against various alternative distributions to evaluate the power of the entropy-based test; however, the use of a theoretical method is more effective to investigate the powers. In this paper, utilizing the information discrimination(ID) index defined by Ehsan et al. (1995) as a mathematical tool, we scrutinize the power of the entropy-based test. The selected alternative distributions are the gamma, Weibull and lognormal distributions, which are widely used in data analysis as an alternative to inverse Gaussian distribution. The study results are provided and an illustrative example is analyzed.

• Journal of the Korean Mathematical Society
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• v.50 no.4
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• pp.879-897
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• 2013

Shannon entropy is one of the widely used randomness measures especially for cryptographic applications. However, the conventional entropy tests are less sensitive to the inter-bit dependency in random samples. In this paper, we propose new online randomness test schemes for true random number generators (TRNGs) based on the mutual information between consecutive ${\kappa}$-bit output blocks for testing of inter-bit dependency in random samples. By estimating the block entropies of distinct lengths at the same time, it is possible to measure the mutual information, which is closely related to the amount of the statistical dependency between two consecutive data blocks. In addition, we propose a new estimation method for entropies, which accumulates intermediate values of the number of frequencies. The proposed method can estimate entropy with less samples than Maurer-Coron type entropy test can. By numerical simulations, it is shown that the new proposed scheme can be used as a reliable online entropy estimator for TRNGs used by cryptographic modules.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.1
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• pp.69-75
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• 2003

In this study, his technique was applied to a GDI spray in order to investigate the mixture distribution. In addition, the homogeneity degree and diffusion effect according to ambient temperature in the high pressure chamber were analyzed by using an entropy analysis method. From this experiment, we could find that entropy analysis is very effective method for the analysis of mixture formation, and the entropy values increase with the progress of uniformity in diffusion Process. we tried to provide the fundamental data for parameter which effects on the spray macroscopic characteristics with mixture ratio of diesel and gasoline. In addition, the mixture formation was analyzed by using entropy analysis. The entropy analysis is based on the concept of statistical entropy, and it identifies the degree of homogeneity in the fuel concentration. From the entropy analysis results we could find that the direct diffusion phenomena is a dominant factor in the formation of a homogeneous mixture at downstream of GDI spray especially in vaporizing conditions. As to increasing ambient temperature and increasing gasoline rate, the entropy intensity using the statistic thermodynamics method is increased because evaporation rate is higher gasoline than diesel.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.4
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• pp.809-826
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• 2018

The entropy evaluation method for noise sources is one of the evaluation methods for the random number generator that is the essential element of modern cryptographic systems and cryptographic modules. The primary entropy evaluation methods outside of the country are more suitable to apply to hardware noise sources than software noise sources, and there is a difficulty in quantitative evaluation of entropy by software noise source. In this paper, we propose an entropy evaluation method that is suitable for software noise sources, considering characteristics of software noise sources. We select time-dependent noise sources that are software noise sources of Windows OS, and the heuristic analysis and experimental analysis are performed considering the characteristics of each time-dependent noise source. Based on these analyses, we propose an entropy harvest method from the noise source and the min-entropy estimation method as the entropy evaluation method for time-dependent noise sources. We also show how to use our entropy evaluation method in the Conditioning Component described in SP 800-90B of NIST(USA).

• 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.