• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.9
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• pp.18-26
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• 1993

This paper presents a multiplier free technique for the complex DFT by rotations and additions based on the complex approximation of the ring of algebraic integers. Speeding-up the computation time and reducing the dynamic range growth has been achieved by the elimination of multiplication. Moreover the DFT of no twiddle factor quantization errors is possible. Numerical examples are given to prove the algorithm and the applicable size of the DFT is 16 has been concluded.

• Journal of applied mathematics & informatics
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• v.14 no.1_2
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• pp.365-376
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• 2004

The purpose of this study is to show that the accuracy of the interpolation method can be at least doubled when additional smoothness requirements and boundary conditions are met. In particular, as a basis function, we are interested in using a conditionally positive definite function $\Phi$ whose generalized Fourier transform is of the form $\Phi(\theta)\;=\;F(\theta)$\mid$\theta$\mid$^{-2m}$ with a bounded function F > 0.

• The Journal of the Acoustical Society of Korea
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• v.23 no.8
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• pp.576-582
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• 2004

A computer code that is based on the Pseudo-spectral finite difference algorithm using staggered grid is developed for the wave propagation modeling in the time domain. The advantage of a finite difference approximation is that any geometrically complicated media can be modeled. Staggered grids are advantageous as it provides much more accuracy than using a regular grid. Pseudo-spectral methods are those that evaluate spatial derivatives by multiplying a wavenumber by the Fourier transform of a pressure wave-field and performing the inverse Fourier transform. This method is very stable and reduces memory and the number of computations. The synthetic results by this algorithm agree with the analytic solution in the infinite and half space. The time domain modeling was implemented in various models. such as half-space. Pekeris waveguide, and range dependent environment. The snapshots showing the total wave-field reveals the Propagation characteristic or the acoustic waves through the complex ocean environment.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.145-155
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• 2015

Noise reduction has been actively studied in the digital image processing and recently, block-based denoising algorithms are widely used. In particular, a low rank approximation employing WNNM(Weighted Nuclear Norm Minimization) and block-based approaches demonstrated the potential for effective noise reduction. However, the algorithm based on low rank a approximation generates the artifacts in the image restoration step. In this paper, we analyzes the image content using the STFT(Short Time Fourier Transform) and proposes an effective method of minimizing the artifacts generated from the conventional algorithm. To evaluate the performance of the proposed scheme, we use the test images containing a wide range of noise levels and compare the results with the state-of-art algorithms.

• Geophysics and Geophysical Exploration
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• v.21 no.1
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• pp.1-7
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• 2018

In the two-dimensional (2D) modeling of electrical method, the potential in the space domain is reconstructed with the calculated potentials in the wavenumber domain using inverse Fourier transform. The inverse Fourier integral is numerically evaluated using the transformed potential at different wavenumbers. In order to improve the precision of the integration, either the logarithmic or exponential approximation has been used depending on the size of wavenumber. Two numerical methods have been generally used to evaluate the integral; interval integration and Gaussian quadrature. However, both methods do not consider the distance from the current source. Thus the resulting potential in the space domain shows some error. Especially when the distance from the current source is very small or large, the error increases abruptly and the evaluated potential becomes extremely unstable. In this study, we developed a new method to calculate the integral accurately by introducing the distance from the current source to the rescaled Gauss abscissa and weight. The numerical tests for homogeneous half-space model show that the developed method can yield the error level lower than 0.4 percent over the various distances from the current source.

• Wind and Structures
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• v.9 no.3
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• pp.231-243
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• 2006

An improvement to the spectral representation algorithm for the simulation of wind velocity fields on large scale structures is proposed in this paper. The method proposed by Deodatis (1996) serves as the basis of the improved algorithm. Firstly, an interpolation approximation is introduced to simplify the computation of the lower triangular matrix with the Cholesky decomposition of the cross-spectral density (CSD) matrix, since each element of the triangular matrix varies continuously with the wind spectra frequency. Fast Fourier Transform (FFT) technique is used to further enhance the efficiency of computation. Secondly, as an alternative spectral representation, the vectors of the triangular matrix in the Deodatis formula are replaced using an appropriate number of eigenvectors with the spectral decomposition of the CSD matrix. Lastly, a turbulent wind velocity field through a vertical plane on a long-span bridge (span-wise) is simulated to illustrate the proposed schemes. It is noted that the proposed schemes require less computer memory and are more efficiently simulated than that obtained using the existing traditional method. Furthermore, the reliability of the interpolation approximation in the simulation of wind velocity field is confirmed.

• The Journal of the Acoustical Society of Korea
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• v.18 no.8
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• pp.48-53
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• 1999

This paper presents an analytic derivation of the erroneous effect when the sliding-DFT is implemented in a recursive way with the finite-bit approximation of the twiddle factors. The analysis result is obtained in a closed form equation of the noise-to-signal power ratio(NSR) employing the zero-mean white Gaussian signal as the target input of the DFT. The parameters of the wordlength used in representing the twiddle factors and the blocklength of the DFT appear in the NSR explicitly as its function variables. The derivation is based on the error dynamic equation which is derived from the recursive SDFT, and on the analytic exploration of the statistical characteristics of the approximation coefficients treating them as random variables of having spatial distributions. The analytically derived results are verified through the comparison with the data actually measured from the computer simulation experiment.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1406-1420
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• 2017

Artificial neural networks (ANNs) play an important role in the fields of function approximation, prediction, and classification. ANN performance is critically dependent on the input parameters, including the number of neurons in each layer, and the optimal values of weights and biases assigned to each neuron. In this study, we apply the particle swarm optimization method, a popular optimization algorithm for determining the optimal values of weights and biases for every neuron in different layers of the ANN. Several regression models, including general linear regression, Fourier regression, smoothing spline, and polynomial regression, are conducted to evaluate the proposed method's prediction power compared to multiple linear regression (MLR) methods. In addition, residual analysis is conducted to evaluate the optimized ANN accuracy for both training and test datasets. The experimental results demonstrate that the proposed method can effectively determine optimal values for neuron weights and biases, and high accuracy results are obtained for prediction applications. Evaluations of the proposed method reveal that it can be used for prediction and estimation purposes, with a high accuracy ratio, and the designed model provides a reliable technique for optimization. The simulation results show that the optimized ANN exhibits superior performance to MLR for prediction purposes.

• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.409-419
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• 2009

In this article, an explicit solution of the EM algorithm for the image deburring is presented. To obtain the restore image from the strictly iterative EM algorithm is quite time-consumed and impractical in particular when the underlying observed image is not small and the number of iterations required to converge is large. The explicit solution provides a quite reasonable restore image although it exploits the approximation in the outside of the valid area of image, and also allows to obtain the effective EM solutions without iteration process in real-time in practice by using the discrete finite Fourier transformation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.6
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• pp.1445-1451
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• 1994

To calculate the wave pressure acting on coastal structures under the design wave condition, it is often necessary to numerically reproduce the big standing wave profiles close to wave breaking condition. For this, the governing equation and all nonlinear terms occurring in boundary conditions should be effectively considered in the numerical wave profile. In particular, the velocity square term in the free surface boundary condition is very important. A boundary element method is applied here to calculate the standing wave profile with the velocity square term fully treated by Newton iterative method. In order to check the validity of the method, the numerical wave profiles are compared to ones calculated by the perturbation method, the Fourier approximation method and the hydraulic experiment.