• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.5
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• pp.18-26
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• 1993

This paper presents the design method for two-dimensional FIR digital filter using optimization scheme. The proposed design method is to extend the optimal one-dimensional filter design algorithm proposed by Parks and McClellan to two-dimensional case. When extending one-dimensional design scheme to two-dimensional one, some problems occur. In this paper we solved the problems by using the least square error model, the two-dimensional Lagrange interpolation, and the modified alternation theory. As a result, the equi-ripple FIR filter is obtained that is more optimal and more specific than the conventional methods.

• Journal of the Chungcheong Mathematical Society
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• v.25 no.2
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• pp.367-377
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• 2012

The goal of the image restoration is to find a good approximation of the original image for the degraded image, the blurring matrix, and the statistics of the noise vector given. Fast truncated Lagrange (FTL) method has been proposed by G. Landi as a image restoration method for large-scale ill-conditioned BTTB linear systems([3]). We implemented FTL method for the image restoration problem with reflective boundary condition which gives better reconstructions of the unknown, the true image.

• Industrial Engineering and Management Systems
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• v.7 no.1
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• pp.9-22
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• 2008

As an extension of a previous work by the authors (Song and Esogbue, 2006), a new algorithm for automated modeling of nonstationary seasonal time series is presented in this paper. Issues relative to the methodology for building automatically seasonal time series models and periodic time series models are addressed. This is achieved by inspecting the trend, estimating the seasonality, determining the orders of the model, and estimating the parameters. As in our previous work, the major instruments used in the model identification process are correlograms of the modeling errors while the least square method is used for parameter estimation. We provide numerical illustrations of the performance of the new algorithms with respect to building both seasonal time series and periodic time series models. Additionally, we consider forecasting and exercise the models on some sample time series problems found in the literature as well as real life problems drawn from the retail industry. In each instance, the models are built automatically avoiding the necessity of any human intervention.

• Journal of the Semiconductor & Display Technology
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• v.18 no.3
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• pp.66-71
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• 2019

In shape from focus (SFF) methods, the quality of image focus volume plays a vital role in the quality of 3D shape reconstruction. Traditionally, a linear 2D filter is applied to each slice of the image focus volume to rectify the noisy focus measurements. However, this approach is problematic because it also modifies the accurate focus measurements that should ideally remain intact. Therefore, in this paper, we propose to enhance the focus volume adaptively by applying 3-dimensional weighted least squares (3D-WLS) based regularization. We estimate regularization weights from the guidance volume extracted from the image sequences. To solve 3D-WLS optimization problem efficiently, we apply a technique to solve a series of 1D linear sub-problems. Experiments conducted on synthetic and real image sequences demonstrate that the proposed method effectively enhances the image focus volume, ultimately improving the quality of reconstructed shape.

• Journal of Korean Academy of Nursing
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• v.39 no.3
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• pp.422-432
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• 2009

Purpose: In this study rest-activity rhythm, sleep pattern and quality of life of patients with restless legs syndrome were compared with those of a normal group. Methods: The participants in this study were 36 patients with restless legs syndrome diagnosed by a neurologist and 36 participants in the normal group. An actigraph, sleep diary, Pittsburgh Sleep Quality Index and Insomnia Severity Index scale were used as measurement tools for the study. Chi-square test, Lamda test, t-test and Kendall's correlation with SPSS 12.0 program were used to analyze the data. Results: Patients with restless legs syndrome had a higher rest-activity rhythm curve of Least 5 hr's activity(L5) and Most 10 hr's activity(M10) than those of normal group and sleep problems included decreased sleep efficiency and increased sleep latency, wake time and number of awakenings. The scores for the subscales of quality of life in patients with restless legs syndrome were lower than the normal group for general health, physical functioning, role limitations due to emotional problems, role limitation due to physical problems, social functioning, bodily pain, vitality and mental health. Conclusion: The results suggest that further studies are needed to identify rest-activity rhythm according to symptom severity and to develop nursing interventions which consider rest-activity rhythm.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.6
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• pp.491-499
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• 2001

In this paper, the scheme of an efficient fuzzy rule generation and fuzzy system construction using GA(genetic algorithm) and FCM(fuzzy c-means) clustering algorithm is proposed for TSK(Takagi-Sugeno-Kang) type fuzzy system. In the structure identification, input data is transformed by PCA(Principal Component Analysis) to reduce the correlation among input data components. And then, a set fuzzy rules are generated for a given criterion by FCM clustering algorithm . In the parameter identification premise parameters are optimally searched by GA. On the other hand, the consequent parameters are estimated by RLSE(Recursive Least Square Estimate) to reduce the search space. From this one can systematically obtain the valid number of fuzzy rules which shows satisfying performance for the given problem. Finally, we applied the proposed method to the Box-Jenkins data and rice taste data modeling problems and obtained a better performance than previous works.

• Progress in Superconductivity
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• v.5 no.1
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• pp.26-30
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• 2003

Magneto-cardiogram(MCG) signals may be highly distorted by the environmental noise, such as power-line interference, broadband white noise, surrounding magnetic noise, and baseline wondering. Several kinds of digital filters and noise cancellation methods have been designed and realized by many researchers, but these methods gave some problems that the original signal may be distorted by digital filter due to the wideband characteristics of background noise. To eliminate noise effectively without distortion of MCG signals, we performed multi-level frequency decomposition using wavelet packets and local adaptive noise cancellation in each local frequency range. In addition to the proposed wavelet filter to eliminate these various non-stationary noise elements, the local adaptive filter using the least mean square(LMS) algorithm and the soft threshold do-noising method are introduced in this paper. The signal to noise ratio(SNR) and the reconstruction square error(RSE) are calculated to evaluate the performance of the proposed method and compared with the results of the conventional wavelet filter and adaptive filter. The experimental results show that the proposed local adaptive filtering method is better than the conventional methods.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.394-396
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• 2006

When developing a new GPS receiver module, the essential problems are evaluation of reliable algorithms, software debugging, and performance comparison between algorithms to find optimal solution. Most GPS receiver modules nowadays use a correlator to track signals from satellites and an MCU (Micro Controller Unit) to control operations of the entire module. The problem of software evaluation from MCU is very difficult, due to limitation of MCU resources and low ability of interfacing with user. Normally, user has to expense special tool kit for a limiting access to MCU but it is also hard to use. This article introduces an implementation of a GPS receiver test bed using correlator GP2021 interfacing with ISA (Industry Standard Architecture) PC bus. This way can give user complete control and visibility into the operation of the receiver, then user can easily debug program and test algorithms. For this article, the least square method is implemented to test the hardware and software performance.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.2
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• pp.13-24
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• 2006

We consider a privacy-preserving cooperative computation protocol evaluating a beneficial function of all participants' secret inputs, such that each party finally holds a share of the function output. We propose a practical privacy-preserving cooperative computation protocol for solving the linear system of equations problem md the linear least-squares problem. Solutions to these problems are widely used in many areas such as banking, manufacturing, and telecommunications. Our multi-party protocol is an efficiently extended version of the previous two-party model.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.583-585
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• 2004

In this paper we will deal with a calibration method for low cost motion capture system using psd(position sensitive detection) optical sensor. To measure the incident direction of the light from LED emitted marker, the PSD is used the output current ratio on the electrode of PSD is proportional with the incident position of the light focused by lens. In order to defect the direction of the light, the current output is converted into digital voltage value by opamp circuits peak detector and AD converter with the digital value the incident position is measured. Unfortunately, due to the non-linearly problem of the circuit poor position accuracy is shown. To overcome such problems, we compensated the non-linearly by using least-square fitting method. After compensated the non-linearly in the circuit, the system showed more enhanced position accuracy.