• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.12C
• /
• pp.1194-1200
• /
• 2006

In this paper, we propose an adaptive MAP (Maximum A Posteriori) high-resolution image reconstruction algorithm using local statistics. In order to preserve the edge information of an original high-resolution image, a visibility function defined by local statistics of the low-resolution image is incorporated into MAP estimation process, so that the local smoothness is adaptively controlled. The weighted non-quadratic convex functional is defined to obtain the optimal solution that is as close as possible to the original high-resolution image. An iterative algorithm is utilized for obtaining the solution, and the smoothing parameter is updated at each iteration step from the partially reconstructed high-resolution image is required. Experimental results demonstrate the capability of the proposed algorithm.

• Journal of Mechanical Science and Technology
• /
• v.17 no.12
• /
• pp.1867-1875
• /
• 2003

In exhaust pipes of automotive engines, the pulsating pressure waves are composed of fundamental frequency and high order harmonics. The nonlinearities in the exhaust pipe is caused by their interactions. The error between prediction and measurement is induced by the nonlinearities. We can not explain this phenomenon using linear acoustics theory. So power spectrum, which is used in linear theory, is not useful. This paper is concerned with the development of useful engineering techniques to detect and analyze nonlinearity in exhaust pipe of automotive engines. The study of higher order statistics has been dominated by work on the bispectrum. The bispectrum can be viewed as a decomposition of the third moment (skewness) of a signal over frequency and as such is blind to symmetric nonlinearities. The phenomenon of quadratic phase coupling (QPC) can be analyzed by the bicoherence function. Finally the application of these techniques to data from actual exhaust pipe systems is performed.

• The Korean Journal of Applied Statistics
• /
• v.31 no.5
• /
• pp.667-675
• /
• 2018

When a financial time series consists of daily (closing) returns, traditional volatility models such as autoregressive conditional heteroskedasticity (ARCH) and generalized ARCH (GARCH) are useful to figure out daily volatilities. With high frequency returns in a day, one may adopt various multivariate GARCH techniques (MGARCH) (Tsay, Multivariate Time Series Analysis With R and Financial Application, John Wiley, 2014) to obtain intraday volatilities as long as the high frequency is moderate. When it comes to the ultra high frequency (UHF) case (e.g., one minute prices are available everyday), a new model needs to be developed to suit UHF time series in order to figure out continuous time intraday-volatilities. Aue et al. (Journal of Time Series Analysis, 38, 3-21; 2017) proposed functional GARCH (fGARCH) to analyze functional volatilities based on UHF data. This article introduces fGARCH to the readers and illustrates how to estimate fGARCH equations using UHF data of KOSPI and Hyundai motor company.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.4
• /
• pp.1866-1883
• /
• 2019

As the youngest branch of information hiding, network covert timing channels conceal the existence of secret messages by manipulating the timing information of the overt traffic. The popular model-based framework for constructing covert timing channels always utilizes cumulative distribution function (CDF) of the inter-packet delays (IPDs) to modulate secret messages, whereas discards high-order statistics of the IPDs completely. The consequence is the vulnerability to high-order statistical tests, e.g., entropy test. In this study, a rich security model of covert timing channels is established based on IPD chains, which can be used to measure the distortion of multi-order timing statistics of a covert timing channel. To achieve rich security, we propose two types of covert timing channels based on nested lattices. The CDF of the IPDs is used to construct dot-lattice and interval-lattice for quantization, which can ensure the cell density of the lattice consistent with the joint distribution of the IPDs. Furthermore, compensative quantization and guard band strategy are employed to eliminate the regularity and enhance the robustness, respectively. Experimental results on real traffic show that the proposed schemes are rich-secure, and robust to channel interference, whereas some state-of-the-art covert timing channels cannot evade detection under the rich security model.

• Genomics & Informatics
• /
• v.14 no.4
• /
• pp.187-195
• /
• 2016

In genetic association studies with high-dimensional genomic data, multiple group testing procedures are often required in order to identify disease/trait-related genes or genetic regions, where multiple genetic sites or variants are located within the same gene or genetic region. However, statistical testing procedures based on an individual test suffer from multiple testing issues such as the control of family-wise error rate and dependent tests. Moreover, detecting only a few of genes associated with a phenotype outcome among tens of thousands of genes is of main interest in genetic association studies. In this reason regularization procedures, where a phenotype outcome regresses on all genomic markers and then regression coefficients are estimated based on a penalized likelihood, have been considered as a good alternative approach to analysis of high-dimensional genomic data. But, selection performance of regularization procedures has been rarely compared with that of statistical group testing procedures. In this article, we performed extensive simulation studies where commonly used group testing procedures such as principal component analysis, Hotelling's $T^2$ test, and permutation test are compared with group lasso (least absolute selection and shrinkage operator) in terms of true positive selection. Also, we applied all methods considered in simulation studies to identify genes associated with ovarian cancer from over 20,000 genetic sites generated from Illumina Infinium HumanMethylation27K Beadchip. We found a big discrepancy of selected genes between multiple group testing procedures and group lasso.

• Journal of Broadcast Engineering
• /
• v.19 no.2
• /
• pp.195-204
• /
• 2014

In this paper, we propose an automatic modulation classification method for ten digitally modulated baseband signals, such as 2-FSK, 4-FSK, 8-FSK, MSK, BPSK, QPSK, 8-PSK, 16-QAM, 32-QAM, and 64-QAM based on higher order statistics of cyclostationary process. The first order cyclic moments and higher order cyclic cumulants of the signal are used as features of the modulation signals. The proposed method consists of two stages. At the first stage, we classify modulation signals as M-FSK and non-FSK using peaks of the first order cyclic moment. At the next step, we apply the Gaussian mixture model-based classifier to classify non-FSK. Simulation results are demonstrated to evaluate the proposed scheme. The results show high probability of classification even in the presence of frequency and phase offsets.

• Proceedings of the KSPS conference
• /
• 2005.04a
• /
• pp.91-94
• /
• 2005

The performance of speech recognition is degraded by the mismatch between training and test environments. Many methods have been presented to compensate for additive noise and channel effect in the cepstral domain, and Cepstral Mean Subtraction (CMS) is the representative method among them. Recently, high order cepstral moment normalization method has introduced to improve recognition accuracy. In this paper, we apply high order moment normalization method and smoothing filter for real-time processing. In experiments using Aurora2 DB, we obtained error rate reduction of 49.7% with the proposed algorithm in comparison with baseline system.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.52 no.5
• /
• pp.305-310
• /
• 2003

In this paper, we proposed an IJADE(Improved joint approximate diagonalisation of eigenmatrices) which use high order statistics instead of second order statistics for data whitening. For simulation, we artificially construct signals mixed with two ECG signals, 60Hz power line interference and 16Hz sine signal and then put them into a JADE and an IJADE. To evaluate the performance of separated ECG signal in each algorithm, we have adopted indices such as kurtosis, standard deviation ratio, correlation coefficient and euclidean distance. As a results, IJ ADE showed theimproved performances as kurtosis of $2\%,$ standard deviation ratio of 0.2194, and Euclidean distance of 0.07 except correlation coefficient showing similar value. In conclusion, the proposed IJADE showed a good performance in separating ECG and a possibilities in applying to the various biological signal.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.12 no.2
• /
• pp.159-165
• /
• 2012

This paper deals with the performance comparison of adaptive equalization algorithm, MMA and SCA, that is used for the minimization of the distortion and noise effect in the communication channel.. The transmitting signal will be distorted and received due to the nonlinearties of magnitude and phase transfer characteristics of communication channel, the compensation of it by using the self adaptive equalizer. The constant modulus has important metric in the self adaptive equalizer, the MMA uses the 2nd and 4th high order statistics of transmitting signal, the SCA uses the 2nd order statistics of transmitting signal only in order to the calculation of it. We compared to the compensation performance of the MMA and SCA by the computer simulation that are possible to the compensation of the two kinds of transfer characteristics at same times by the relatively simple arithmatic operation. We used to the recovered constellation, residual isi and MSE, SER that are the essential index for the comparison of the adaptive equalizer. The result of performance comparison of algorithms, the MMA which uses the high order statistics of transmitting signal has good performance in the MSE and SER compared to the SCA which is using the low order statistics. But in the recovered costellation and residual isi, the SCA has a good than the MMA.

• Communications for Statistical Applications and Methods
• /
• v.4 no.1
• /
• pp.185-191
• /
• 1997

Bayesian estimation of multinomial and Poisson parameters under starshped restriction is considered. Most Bayesian estimations in order restricted statistical inference require the high-dimensional integration which is very difficult to evaluate. Monte Carlo integration and Gibbs sampling are among alternative methods. The Bayesian estimation considered in this paper requires only evaluation of incomplete beta functions which are extensively tabulated.