• The Korean Journal of Applied Statistics
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• v.18 no.2
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• pp.253-269
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• 2005

One of the basic assumptions of the regression models is that the parameter vector does not vary across sample observations. If the parameter vector is not constant for all observations in the sample, the statistical model is changed and the usual least squares estimators do not yield unbiased, consistent and efficient estimates. This study investigates the regression model with some or all parameters vary across partitions of the whole sample data when the model permits different response coefficients during unusual time periods. Since the usual test for overall homogeneity of regressions across partitions of the sample data does not explicitly identify the break points between the partitions, the testing the equality between subsets of coefficients in two or more linear regressions is generalized and combined with the test procedure to search the break point. The method is applied to find the possibility and the turning point of the structural change in the long-run unemployment rate in the usual static framework by using the regression model. The relationships between the variables included in the model are reexamined in the dynamic framework by using Vector Autoregression.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.4
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• pp.264-274
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• 2003

This paper presents a direct generalized minimum-variance self tuning controller with a PID structure using neural network which adapts to the changing parameters of the nonlinear system with nonminimum phase behavior, noises and time delays. The self-tuning controller with a PID structure is a combination of the simple structure of a PID controller and the characteristics of a self-tuning controller that can adapt to changes in the environment. The self-tuning control effect is achieved through the RLS (recursive least square) algorithm at the parameter estimation stage as well as through the Robbins-Monro algorithm at the stage of optimizing the design parameter of the controller. The neural network control effect which compensates for nonlinear factor is obtained from the learning algorithm which the learning error between the filtered reference and the auxiliary output of plant becomes zero. Computer simulation has shown that the proposed method works effectively on the nonlinear nonminimum phase system with time delays and changed system parameter.

• The Journal of the Acoustical Society of Korea
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• v.7 no.4
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• pp.98-109
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• 1988

This paper introduces an adaptive nonlinear filtering algorithm that uses the sequential regression(SER) method to update the second order Volterra filter coefficients in a recursive way. Conventionally, the SER method has been used to invert large matrices which result from direct application of Wiener filter theory to the Volterra filter. However, the algorithm proposed in this paper uses the SER approach to update the least squares solution which is derived for Gaussian input signals. In such an algorithm, the size of the matrix to be inverted is smaller than that of conventional approaches, and hence the proposed method is computationally simpler than conventional nonlinear system identification techniques. Simulation results are presented to demonstrate the performance of the proposed algorithm.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.2
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• pp.97-105
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• 2015

This paper discusses the implementation of Bruun's FFT on a SIMD processor. FFT is an algorithm used in digital signal processing area and its effective processing is important in the enhancement of signal processing performance. Bruun's FFT algorithm is one of fast Fourier transform algorithms based on recursive factorization. Compared to popular Cooley-Tukey algorithm, it is advantageous in computations because most of its operations are based on real number multiplications instead of complex ones. However it shows more complicated data alignment patterns and requires a larger memory for storing coefficient data in its implementation on a SIMD processor. According to our experiment result, in the processing of the FFT with 1024 complex input data on a SIMD processor, The Bruun's algorithm shows approximately 1.2 times higher throughput but uses approximately 4 times more memory (20 Kbyte) than the Cooley-Tukey algorithm. Therefore, in the case with loose constraints on silicon area, the Bruun's algorithm is proper for the processing of FFT on a SIMD processor.

• Journal of IKEEE
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• v.8 no.1 s.14
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• pp.128-135
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• 2004

This paper proposes a phase measurement algorithm which is based on the recursive implementation of sliding-DFT. The algorithm is designed to have a robust behavior against the erroneous factors of frequency drift, additive noise, and twiddle factor approximation. The size of phase error caused by the finite wordlength implementation of DFT twiddle factors is shown significantly lower than that of magnitude error. The drastic reduction of the phase error is achieved by the exploitation of the quadruplet symmetry characteristics of the approximated twiddle factors in the complex plane. Four channel power-line phase measurement system is also designed and implemented based on the time-multiplexed sharing architecture of the proposed algorithm. The operation of the developed system is also verified by the experiment performed under the test environment implemented with the multi-channel function generator and the on-line interfaced host processor system. The proposed algorithm's features of phase measurement accuracy and its robustness against the finite wordlength effects can provide a significant impact especially for the ASIC or microprocessor based embedded system applications where the enhanced processing speed and implementation simplicity are crucial design considerations.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.2
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• pp.186-192
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• 2011

In this paper, we propose a new procedure for improvement of the linear predictive coding. To reduce the error power incurred by the coding, we interchanged the order of the two procedures of windowing on the signal and linear prediction. This scheme corresponds to LPC extraction with windowed autocorrelation. The proposed method requires more calculational time because it necessitates matrix inversion on more parameters than the conventional technique where an efficient Levinson-Durbin recursive procedure is applicable with smaller parameters. Experimental test over various speech phonemes showed, however, that our procedure yields about 5 % less power distortion compared to the conventional technique. Consequently, the proposed method in this paper is thought to be preferable to the conventional technique as far as the fidelity is concerned. In a separate study of speaker-dependent speech recognition test for 50 isolated words pronounced by 40 people, our approach yielded better performance too.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.681-684
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• 2015

Power amplifier is an essential component for transmitting signals to a remote receiver in wireless communication systems. Power amplifier is a non-linear device in general, and the nonlinear distortion becomes severer as the output power increases. The nonlinearity results in spectral regrowth, which leads to adjacent channel interference, and decreases the transmit signal quality. To linearize power amplifiers, many techniques have been developed so far. Among the techniques, digital pre-distortion is known as the most cost and performance effective technique. However, the linearization performance falls down abruptly when the power amplifier operates in its saturation region. This is because of the severe nonlinearity. To relieve this problem, this paper proposes a new adaptive predistortion technique. The proposed technique controls the adaptive algorithm based on the power amplifier input level. Specifically, for small signals, the adaptive predistortion algorithm works normally. On the contrary, for large signals, the adaptive algorithm stops until small signals occur again. By doing this, wrong coefficient update by severe nonlinearity can be avoided. Computer simulation results show that the proposed method can improve the linearization performance compared with the conventional digital predistortion algorithms.

• The Transactions of the Korean Institute of Power Electronics
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• v.8 no.1
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• pp.80-88
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• 2003

In this paper, the new robust torsional vibration suppression control scheme is proposed for the two mass system. A reduced order state feedback controller where the motor speed and the observed torsional torque are fed back and the PI controller are proposed as the torsional vibration suppression controller. Using the estimated mechanical parameters by off-line RLS(Recursive Least Square) algorithms, the speed controller for torsional vibration suppression is designed and its gains are determined using the Kharitonov robust control theory. The Kharitonov robust control theory can obtain the robust stability with a specified stability margin and a damping limit and the good performance of vibration suppression although if the parameters are varied within some specified limit. The effectiveness and usefulness of the proposed schemes are verified with the simulation and the experimental results on the fully-digitalized 5.5kW two mass system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6A
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• pp.524-532
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• 2002

This paper reports that the Lambert W function applies to a non-iterative design of minimum mean square-error scalar quantizers for a Laplacian source. Specifically, it considers a non-iterative design algorithm for optimum quantizers for a Laplacian source; it finds that the solution of the recursive nonlinear equation in the non-iterative design is elegantly expressed in term of the principal branch of the Lambert W function in a closed form; and it proves that the non-iterative algorithm applies only to exponential or Laplacian sources. The contribution of the paper is in the reduction of the time needed for the design and the increased accuracy in resulting quantization points and thresholds, because the algorithm is non-iterative and the Lambert W function can be evaluated as accurately as desired. Also, numerical results show how optimal quantization distortion converges monotonically to the Panter-Dite constant and help derive an approximation formula for the key parameters of optimum quantizers.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1447-1454
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• 2013

In this study, we developed the equation of ship wave crests in intermediate as well as deep waters by extending Kelvin's (1887) theory using the recursive relation for the dispersion relation. The present equation can be applied for varying water depth as well as constant water depth. Using FLOW-3D we conducted numerical experiments to verify analytical prediction. The ship wave crest patterns became asymmetric on a plane slope when the ship propagates alongshore direction. That is, in shallower side, wave crests tend to be parallel to the coastline due to refraction and, in deeper side, wave crests tend to be orthogonal due to reverse refraction.