• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.5
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• pp.58-64
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• 2004

A new method to obtain approximate solutions by placing the only poles of the slow subsystem for the two-time-scale aircraft dynamic systems. The two kinds of approximate solutions are obtained by a matrix block diagonalization. One is called the uncorrected solution, and the other is called the corrected solution. The former has an error of $O({\varepsilon})$, and the latter has an error of $O({\varepsilon}^2)$. Of course, both solutions are robust enough even though they are reduced solutions. The excellence of the proposed method is illustrated by an numerical example of an aircraft longitudinal dynamics.

• Bulletin of the Korean Chemical Society
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• v.24 no.8
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• pp.1097-1101
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• 2003

The cubic and quartic anharmonic force field of malonaldehyde is calculated using density functional theory at the B3LYP/6-31G(d,p) level, and used to simulate coherent infrared vibrational spectra. 12 normal modes are included in the simulation, and the Arnoldi method is employed for the diagonalization of the Hamiltonian. The calculated three pulse infrared signals in the k1 + k2 - k3 direction show signatures of the intramolecular hydrogen bond couplings between the C=O stretch, H-O-C bend and O-H stretch vibrations.

• Journal of applied mathematics & informatics
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• v.23 no.1_2
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• pp.25-42
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• 2007

A direct solver for the Legendre tau approximation for the two-dimensional Poisson problem is proposed. Using the factorization of symmetric eigenvalue problem, the algorithm overcomes the weak points of the Schur decomposition and the conventional diagonalization techniques for the Legendre tau approximation. The convergence of the method is proved and numerical results are presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12A
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• pp.1006-1013
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• 2009

This paper proposes a data stream allocation technique for fair capacity performance in multiuser multiple-input multiple-output (MIMO) systems using block diagonalization (BD) algorithm. Conventional studies have been focused on maximum sum capacity. Thus, there is a very large difference of capacity among users, since user capacity unfairly distributed according to each user channel environment. In additional, poor channel user has very small capacity, since base station allocates the power by using water-filling technique. Also, almost studies limited itself to obtain the additional gain by using the same number of data streams for all users. In this paper, we propose the technique for maximizing sum capacity under the fair performance constraint by allocating data stream according to user channel environment. Also, proposed algorithm has more gain of sum capacity and transmit power than conventional equal allocation via computer simulation.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.209-211
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• 2007

The computational time of Stocahstic Diagonalization (SD) calculation for 2-dimensional interacting fermion systems is reduced by using several methods including symmetry operations. First, each lattice is subdivided into spin-up and spin-down lattices separately, thus allowing a bi-partite lattice. A valid basis state is then obtained from stacking up an up-spin configuration on top of a down-spin configuration. As a consequence, the memory space to be used in saving the trial basis state reduces significantly. Secondly, the matrix elements of a Hamiltonianin are reconrded in a look-up table when making basis state set. Thus the repeated calculation of the matrix elements of the Hamiltonian are avoided during SD process. Thirdly, by applying symmetry operations to the basis state set the original basis state is transformed to a new basis state whose elements are the eigenvectors of the symmetry operations. The ground state wavefunction is constructed from the elements of symmetric - bonding state - basis state set. As a result, the total number of basis states involved in SD calculation is reduced upto 50 percentage by using symmetry operations.

• The Journal of the Acoustical Society of Korea
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• v.38 no.2
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• pp.177-183
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• 2019

In this paper, we proposed an application method of ICA (Independent Component Analysis) to passive line array sonar to separate interferences from target signals in low frequency band and compared performance of three conventional ICA algorithms. Since the low frequency signals are received through larger bearing angles than other frequency bands, neighboring beam signals can be used to perform ICA as measurement signals of the ICA. We use three ICA algorithms such as Fast ICA, NNMF (Non-negative Matrix Factorization) and JADE (Joint Approximation Diagonalization of Eigen-matrices). Through experiments on real data obtained from passive line array sonar, it is verified that the interference can be separable from target signals by the suggested method and the JADE algorithm shows the best separation performance among the three algorithms.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.553-556
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• 2000

This paper proposes an adaptive linearization method of Volterra nonlinear systems using DWT(Discrete Wavelet Transform)and an LMS-type predistorter. In particular, the proposed wavelet transform-domain lineatization method leads to diagonalization of the input vector auto-correlation matrix which yields improvement of the convergence rate of the corresponding transform-domain LMS algorithm. Furthermore, the adaptive Volterra predistorter followed by a corresponding weakly Volterra nonlinear system(here. a TWT amplifier model in a satellite communication system) is utilized to compensate for the distortion in the output. Also,12-PSK and 4-QAM are applied as the input to the nonlinear system to be tested. Some simulation results show that the proposed linearization approach has better performance than DCT-based or conventional normalized LMS algorithms do.

• ETRI Journal
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• v.36 no.1
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• pp.175-178
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• 2014

We introduce the Energy-Based Blind Separating (EBS) algorithm for extremely fast separation of mixed speech signals without loss of quality, which is performed in two stages: iterative-form separation and closed-form separation. This algorithm significantly improves the separation speed simply due to incorporating only some specific frequency bins into computations. Simulation results show that, on average, the proposed algorithm is 43 times faster than the independent component analysis (ICA) for speech signals, while preserving the separation quality. Also, it outperforms the fast independent component analysis (FastICA), the joint approximate diagonalization of eigenmatrices (JADE), and the second-order blind identification (SOBI) algorithm in terms of separation quality.

• Journal of Korean Society of Transportation
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• v.14 no.3
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• pp.27-44
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• 1996

The purpose of the thesis is providing a new formulation for the transit assignment problem. The existing models dealing with the transit assignment problem don't consider the congestion effects due to the insufficient capacity of transit vehicles. Besides, these models don't provide solutions satisfying the Wardrop's user equilibrium conditions. The congestion effects are considered to be concentrated at the transit stops. For the transit lines, the waiting times at the transit stops are dependent on the passenger flows. The new model suggests the route section cost function analogous to the link performance function of the auto assignment to reflect the congestion effects in congested transit network. With the asymmetric cost function, the variational inequality programming is used to obtain the solutions satisfying Wardrop's condition. The diagonalization algorithm is introduced to solve this model. Finally, the results are compared with those of EMME/2.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.5
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• pp.415-419
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• 2001

This paper proposes and adaptive nonlinear equalizer based on Volterra Series along with M-band wavelet transform(M-DWT). The proposed wavelet transform-domain approach leads to diagonalization of the input vector auto-correlation matrix, which yields clustering its eigenvalue spread around one, and improving the convergence rate of the corresponding transform-domain LMS algorithm. In particular, the proposed adaptive Volterra equalizer is employed to compensate for the output distortion produced by a weakly nonlinear system. Finally, some simulation results obtained by using a TWT amplifier model are provide to demonstrated the converging performance of the proposed approach.