• The Journal of the Acoustical Society of Korea
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• v.25 no.1E
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• pp.8-13
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• 2006

In this paper, an Optimized Ambisonic Panning Algorithm (OAPA) which reduces sound localization error, is proposed. In the conventional Ambisonic Panning Algorithm (APA), sound localization is usually different from the panning angle, especially when listeners are not in an ideal listening position, because of low signal separation among other channels. To overcome this problem, an OAPA using window functions is proposed. A proper window function can be verified, comprising of higher harmonic components than 2M+1 and improved DPC and channel separation. Analysis results demonstrate that the proposed method results in higher signal separation among other channels and lower sound localization errors than the conventional APA.

• MALSORI
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• no.67
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• pp.195-216
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• 2008

This paper addresses the problem of single-channel speech separation to extract the speech signal uttered by the speaker of interest from a mixture of speech signals. We propose to apply time-frequency smoothing to the existing statistical single-channel speech separation algorithms: The soft mask and the minimum-mean-square-error (MMSE) algorithms. In the proposed method, we use the two smoothing later. One is the uniform mask filter whose filter length is uniform at the time-Sequency domain, and the other is the met-scale filter whose filter length is met-scaled at the time domain. In our speech separation experiments, the uniform mask filter improves speaker-to-interference ratio (SIR) by 2.1dB and 1dB for the soft mask algorithm and the MMSE algorithm, respectively, whereas the mel-scale filter achieves 1.1dB and 0.8dB for the same algorithms.

• Journal of KIEE
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• v.10 no.1
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• pp.7-15
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• 2000

Source separation is a statistical method, the goal of which is to separate the linear instantaneous mixtures of statistically independent sources without resorting to any prior knowledge. This paper addresses a source separation algorithm which is able to separate the mixtures of sub- and super-Gaussian sources. The nonlinear function in the proposed algorithm is derived from the generalized Gaussian distribution that is a set of distributions parameterized by a real positive number (Gaussian exponent). Based on the relationship between the kurtosis and the Gaussian exponent, we present a simple and efficient way of selecting proper nonlinear functions for source separation. Useful behavior of the proposed method is demonstrated by computer simulations.

• ETRI Journal
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• v.27 no.3
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• pp.294-303
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• 2005

In this paper, a supervised algorithm for the evaluation of geophysical sites using a multi-level cellular neural network (ML-CNN) is introduced, developed, and applied to real data. ML-CNN is a stochastic image processing technique based on template optimization using neighborhood relationships of the pixels. The separation/enhancement and border detection performance of the proposed method is evaluated by various interesting real applications. A genetic algorithm is used in the optimization of CNN templates. The first application is concerned with the separation of potential field data of the Dumluca chromite region, which is one of the rich reserves of Turkey; in this context, the classical approach to the gravity anomaly separation method is one of the main problems in geophysics. The other application is the border detection of archeological ruins of the Hittite Empire in Turkey. The Hittite civilization sites located at the Sivas-Altinyayla region of Turkey are among the most important archeological sites in history, one reason among others being that written documentation was first produced by this civilization.

• Tribology and Lubricants
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• v.36 no.6
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• pp.324-331
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• 2020

Wedging in a frictional elastic system is defined if the state of stick exists after the external loading on the system is removed. This paper presents a method to determine the critical coefficient of wedging for an elastic frictional system by considering the separation state. Wedging is always possible if the coefficient of friction exceeds a critical value known as the critical wedging coefficient. This method requires two concepts: a necessary and sufficient condition for wedging, which can be interpreted as positive spanning sets of constraint vectors existing in the wedged system, and the minimal positive basis that enables a minimum wedging coefficient. The algorithm based on the positive spanning concept is repeatedly executed after eliminating nodes from the contact stiffness matrix, for which the separation states are impending. The simulation results show that once a node enters the separation state, it never returns to the contact state again and the critical wedging coefficient reduces during repeated algorithm execution. The benefit of this method is that the computation time permits handling models with large numbers of contact nodes. The algorithm can also numerically find the critical wedging coefficient, thereby contributing to fastening and assembly performance improvements in mechanical systems.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3291-3300
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• 2023

Recently molybdenum alloys have been introduced as accident tolerating materials for cladding of fuel rods. Molybdenum element has seven stable isotopes with different neutron absorption cross section used in various fields, including nuclear physics and radioisotope production. This study presents separation approaches for all intermediate isotopes of molybdenum element by squared-off cascades using a newly developed numerical code with Salp Swarm Algorithm (SSA) optimization algorithm. The parameters of cascade including feed flow rate, feed entry stage, cascade cut, input feed flow rate to gas centrifuges (GCs), and cut of the first stage are optimized to maximize both isotope recovery and cascade capacity. The squared off and squared cascades are studied, and the efficiencies are compared. The results obtained from the optimization showed that for the selected squared off cascade, Mo⁹⁴ in four separation steps, Mo⁹⁵ in five steps, Mo⁹⁶ in six steps, Mo⁹⁷ in seven steps, and Mo⁹⁸ in two steps are separated to the desired concentrations. The highest recovery factor is obtained 63% for Mo⁹⁴ separation and lowest recovery factor is found 45% for Mo⁹⁵.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.3
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• pp.198-205
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• 2005

In this paper, we proposed a new algorithm for the separation of fetal ECG from single channel abdominal ECG. The algorithm consists of a stage of demixing vector calculation for initial signal and a stage of fetal beat detection for the rest of signal. The demixing vector was obtained by applying independent component analysis technique to projected signals into time-frequency domain. For the test of this algorithm, simulation signals, De Lathauwer's data and some measured data, which was acquired from 8 healthy volunteers whose pregnant periods ranged from 22 weeks to 35 weeks and whose ages from 27 to 37, were used. For each data, the accuracy of fetal beat detection was $100\%$ and with the location of fetal beats, fetal heart rate variability and morphology could be offered. In conclusion, this proposed algorithm showed the possibility of fetal beat separation with a single channel abdominal ECG and it might be adopted to a fetal health monitoring system, by which a single channel abdominal ECG is acquired.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.5
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• pp.48-55
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• 2009

In this paper, We propose Adaptive Group Separation algorithm for efficient RFID system AGS algorithm determines the optimized initial prefix size j, and divides the group of. A reader requests the group and searches the tag ID. If a tag collision occurred, reader adds a one bit, '0' or '1' at first bit of collision point, As a result we observe that transmitted data bits and the recognition time are decreased. The proposed algorithms have been verified by computer simulation. The performance of the proposed anti-collision algorithm is evaluated in terms of the number of repetitions and the amount of transmission bits according to the in crease of the number of tags is 256. The AGS algorithm improve the number of repetitions by about 32.3% and reduce tile amount of the transmission bits by about 1/40 than slotted binary tree algorithm.

• Geophysics and Geophysical Exploration
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• v.18 no.2
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• pp.74-84
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• 2015

To yield physically meaningful images through elastic reverse-time migration, the wavefield separation which extracts P- and S-waves from reconstructed vector wavefields by using elastic wave equation is prerequisite. For expanding the application of the elastic reverse-time migration to anisotropic media, not only the anisotropic modelling algorithm but also the anisotropic wavefield separation is essential. The anisotropic wavefield separation which uses pseudo-derivative filters determined according to vertical velocities and anisotropic parameters of elastic media differs from the Helmholtz decomposition which is conventionally used for the isotropic wavefield separation. Since applying these pseudo-derivative filter consumes high computational costs, we have developed the efficient anisotropic wavefield separation algorithm which has capability of parallel computing by using GPUs (Graphic Processing Units). In addition, the highly efficient anisotropic elastic reverse-time migration algorithm using MPI (Message-Passing Interface) and incorporating the developed anisotropic wavefield separation algorithm with GPUs has been developed. To verify the efficiency and the validity of the developed anisotropic elastic reverse-time migration algorithm, a VTI elastic model based on Marmousi-II was built. A synthetic multicomponent seismic data set was created using this VTI elastic model. The computational speed of migration was dramatically enhanced by using GPUs and MPI and the accuracy of image was also improved because of the adoption of the anisotropic wavefield separation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.2
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• pp.237-245
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• 2012

This paper describes an acoustic echo canceller with double-talk by the blind signal separation. The acoustic echo canceller is deteriorated or diverged in the double-talk period. So we use the blind signal separation to estimate the near-end speech signal and to eliminate the estimated signal from the residual signal. The blind signal separation extracts the near-end signal with dual microphones by the iterative computations using the 2nd order statistical character. Because the mixture model of blind signal separation is multi-channel in the closed reverberation environment, we used the copied coefficients of echo canceller without computing the separation coefficients. By this method, the acoustic echo canceller operates irrespective of double-talking. We verified performances of the proposed acoustic echo canceller by simulations. The results show that the acoustic echo canceller with this algorithm detects the double-talk periods thoroughly, and then operates stably in the normal state without the divergence of coefficients after ending the double-talking. And it shows the ERLE of averagely 20dB higher than the normal LMS algorithm.