• MALSORI
• /
• no.66
• /
• pp.105-116
• /
• 2008

In this research, we propose a speaker identification system using a kernel method which is expected to model the non-linearity of speech features well. We have been using principal component analysis (PCA) successfully, and extended to kernel PCA, which is used for many pattern recognition tasks such as face recognition. However, we cannot use kernel PCA for speaker identification directly because the storage required for the kernel matrix grows quadratically, and the computational cost grows linearly (computing eigenvector of $l{\times}l$ matrix) with the number of training vectors I. Therefore, we use greedy kernel PCA which can approximate kernel PCA with small representation error. In the experiments, we compare the accuracy of the greedy kernel PCA with the baseline Gaussian mixture models using MFCCs and PCA. As the results with limited enrollment data show, the greedy kernel PCA outperforms conventional methods.

• Journal of the Korean Vacuum Society
• /
• v.8 no.4B
• /
• pp.556-564
• /
• 1999

The analysis on heat fluxed on and transmission efficiencies by the collimators of neutral beam injection lines in KSTAR tokamak device has been carried out. And a mathematical model describing non-Gaussian beam distribution profile has been established. A neutral beam injection device is composed of 3 separate ion sources and corresponding beam transport lines, which deal with 7.8 MW of beam power, respectively. The divergence angles of ion beam are $1.2^{\circ}$and $0.5^{\circ}$, in vertical and horizontal directions, respectively. The maximum normal heat load on source exit scraper is 9.1 kW/$\textrm{cm}^2$ and net beam transmission efficiency is ~28%. The effect of misalignment of ion source and scrapers on the scraper heat load and beam transmission also has been analyzed.

• Publications of The Korean Astronomical Society
• /
• v.7 no.1
• /
• pp.51-61
• /
• 1992

The nonlinear stochastic behavior of chaotic inflation is characterized by the 'scaling' effect. Using a simple criterion for the appearance of scaling behavior in the ${\lambda}{\phi}^4$ inflation model, we show explicitly that in this limit the onset of the scaling regime does not require any special initial conditions and that it is independent of the self-coupling constant ${\lambda}$. Non-Gaussian statistics in adiabatic fluctuations are important only for super-horizon scales and the scaling regime does not lead to any significant statistical properties on currently observable scales. However, the scaling effect gives some cosmological consequences very different from what we expect in the naive diffusion approximation for quantum fluctuations. The classical (deterministic) treatment of the inflation field (essentially a quantum mechanical object.) becomes valid towards the end of inflation.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.9 no.6
• /
• pp.1341-1345
• /
• 2005

Sequential Monte Carlo techniques are a set of powerful and versatile simulation-based methods to perform optimal state estimation in nonlinear non-Gaussian state-space models. We can use Monte Carlo particle filters adaptively, i.e. so that they simultaneously estimate the parameters and the signal. However, Sequential Monte Carlo techniques require the use of special panicle filtering techniques which suffer from several drawbacks. We consider here an alternative approach combining particle filtering and Sequential Hybrid Monte Carlo. We give some examples of applications in fisheries(luespotted mud hopper data).

• MALSORI
• /
• no.63
• /
• pp.139-151
• /
• 2007

As the Internet becomes prevalent in our lives, harmful contents, such as phornographic videos, have been increasing on the Internet, which has become a very serious problem. To prevent such an event, there are many filtering systems mainly based on the keyword-or image-based methods. The main purpose of this paper is to devise a system that classifies pornographic videos based on the audio information. We use the mel-cepstrum modulation energy (MCME) which is a modulation energy calculated on the time trajectory of the mel-frequency cepstral coefficients (MFCC) as well as the MFCC as the feature vector. For the classifier, we use the well-known Gaussian mixture model (GMM). The experimental results showed that the proposed system effectively classified 98.3% of pornographic data and 99.8% of non-pornographic data. We expect the proposed method can be applied to the more accurate classification system which uses both video and audio information.

• ETRI Journal
• /
• v.9 no.3
• /
• pp.3-12
• /
• 1987

In this paper, a non-classical autocorrelation detector adopting a newly defined test statistic is introduced to solve the typical problem of detecting a narrowband signal transmitted over an additive white Gaussian noise (AWGN) channel. Error probability analyses are performed for a noncoherent frequency-shift-keying (FSK) system employing the proposed test-statistic. Through the histogram approach, the probability density functions of the test-statistics are plotted to explain the analysis model. All numerical results obtained indicate the limited improvement in error performance under the lower signal-to-noise ratio (SNR) and the use of higher number of samples per bit will finally provide the almost same confident potential of improvement in error rate as the system using matched filters (MFs) gives.

• Communications for Statistical Applications and Methods
• /
• v.29 no.2
• /
• pp.277-286
• /
• 2022

Due to the uniquely slow convergence speed of the EM algorithm, it suffers form a lot of processing time until the desired deconvolution image is obtained when the image is large. To cope with the problem, in this paper, an immediate solution of the EM algorithm is provided under the Gaussian image model. It is derived by finding the recurrent formular of the EM algorithm and then substituting the results repeatedly. In this paper, two types of immediate soultion of image deconboution by EM algorithm are provided, and both methods have been shown to work well. It is expected that it free the processing time of image deconvolution because it no longer requires an iterative process. Based on this, we can find the statistical properties of the restored image at specific iterates. We demonstrate the effectiveness of the proposed method through a simple experiment, and discuss future concerns.

• Journal of Communications and Networks
• /
• v.17 no.1
• /
• pp.21-26
• /
• 2015

The general wiretap channel with noiseless feedback is first investigated by Ahlswede and Cai, where lower and upper bounds on the secrecy capacity are provided in their work. The upper bound is met with equality only in some special cases. In this paper, we study a special case of the general wiretap channel with noiseless feedback (called non-degraded wiretap channel with noiseless feedback). Inner and outer bounds on the capacity-equivocation region of this special model are provided. The outer bound is achievable if the main channel is more capable than the wiretap channel. The inner bound is constructed especially for the case that the wiretap channel is more capable than the main channel. The results of this paper are further explained via binary and Gaussian examples. Compared with the capacity results for the non-degraded wiretap channel, we find that the security is enhanced by using the noiseless feedback.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.61 no.12
• /
• pp.1920-1925
• /
• 2012

In this paper, we propose a novel method to improve the performance of the improved minima controlled recursive averaging (IMCRA) in non-stationary noisy environment. The conventional IMCRA algorithm efficiently estimate the noise power by averaging past spectral power values based on a smoothing parameter that is adjusted by the signal presence probability in frequency subbands. Since the minimum of smoothing parameter is defined as 0.85, it is difficult to obtain the robust estimates of the noise power in non-stationary noisy environments that is rapidly changed the spectral characteristics such as babble noise. For this reason, we proposed the modified IMCRA, which adaptively estimate and updata the noise power according to the noise type classified by the Gaussian mixture model (GMM). The performances of the proposed method are evaluated by perceptual evaluation of speech quality (PESQ) and composite measure under various environments and better results compared with the conventional method are obtained.

• The Bulletin of The Korean Astronomical Society
• /
• v.46 no.1
• /
• pp.47.2-47.2
• /
• 2021

Focusing on both small separations and baryonic acoustic oscillation scales, the cosmic evolution of the clustering properties of peak, void, wall, and filament-type critical points is measured using two-point correlation functions in ΛCDM dark matter simulations as a function of their relative rarity. A qualitative comparison to the corresponding theory for Gaussian random fields allows us to understand the following observed features: (i) the appearance of an exclusion zone at small separation, whose size depends both on rarity and signature (i.e. the number of negative eigenvalues) of the critical points involved; (ii) the amplification of the baryonic acoustic oscillation bump with rarity and its reversal for cross-correlations involving negatively biased critical points; (iii) the orientation-dependent small-separation divergence of the cross-correlations of peaks and filaments (respectively voids and walls) that reflects the relative loci of such points in the filament's (respectively wall's) eigenframe. The (cross-) correlations involving the most non-linear critical points (peaks, voids) display significant variation with redshift, while those involving less non-linear critical points seem mostly insensitive to redshift evolution, which should prove advantageous to model. The ratios of distances to the maxima of the peak-to-wall and peak-to-void over that of the peak-to-filament cross-correlation are ~2-√~2 and ~3-√~3WJ, respectively, which could be interpreted as the cosmic crystal being on average close to a cubic lattice. The insensitivity to redshift evolution suggests that the absolute and relative clustering of critical points could become a topologically robust alternative to standard clustering techniques when analysing upcoming surveys such as Euclid or Large Synoptic Survey Telescope (LSST).