• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.4
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• pp.328-331
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• 2019

A linear frequency modulated pulse train waveform can be cost-effective in achieving high range resolution, and thus the synthetic aperture radar may be benefited by using the mixer output of the received signal. However, the image formation process from a mixer output is vulnerable to errors caused by stop-and-go approximation. In this paper, a nadir-looking imaging radar based on time domain correlation is proposed. Furthermore, to prevent the occurrence of ghosting effect in images, antenna placement on a rotating disk is proposed. Simulation results indicate that ghosting effect can be eliminated by employing the proposed antenna placement structure.

• Journal of the Korea Computer Graphics Society
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• v.5 no.1
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• pp.1-9
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• 1999

본 논문은 곡률 오차에 의해 간략화 된 메쉬에 계층적 계산을 이용하여 다단계 메쉬를 생성하는 알고리즘을 제안한다. 본 논문의 알고리즘으로 생성된 계층적 계산 구조의 다단계 메쉬는 임의의 메쉬의 분할 연결성 생성을 위한 분할 메쉬로의 근사 과정이 생략 가능하므로, 다단계 메쉬 생성 속도의 향상을 도모할 수 있다. 또한 분할 연결성이 없는 계층적 계산 구조의 다단계 메쉬는 간략화 메쉬들의 단순 축적이 아닌 간략화 메쉬의 단계 사이를 계층적 계산으로 얻어지는 계수들과 가장 간략화 된 메쉬로 구성됨으로써 다면체 압축 및 다단계 편집에 유효한 다단계 메쉬 생성이 가능하다.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.37 no.11
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• pp.23-31
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• 2000

In the layered medium, infinite Sommerfeld integral must be evaluated to calculate a space domain Green's function. The complex image method and the two-level method provide rapid calculation and accurate solutions in the near-field region. However, in the intermediate and far-field region, the solutions are inaccurate due to the deformation of the sampling contour. In this paper, we propose a method to calculate an accurate closed-form Green's function for coplanar structure by sampling data on the real axis.

• Journal of the KSME
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• v.22 no.6
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• pp.456-462
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• 1982

재래의 공학적 해석과정에서는, 주어진 시스템에 대한 정량적 해석을 위해 우선 시스템에 대한 수학적 모형을 가정.도입하고, 미지계수에 대한 결정은 시스템으로부터 관측된 자료에 의존하게 된다. 반면 DDS에 의한 모형화는 시스템에 대한 사전 지식이 없어도 시스템으로부터의 자료에 대한 체계적인 정량적 해석을 통해서 시스템을 특성화시키는 미분방정식을 유도할 수 있게 하며 오히려 시스템에 대한 이해를 돕게 한다. 이 때 결정되는 모형은 최소오차자승법(least square error method)에 의한 통계학적으로 가장 적합한 근사모형으로 결정된 모형의 계수로부터 시 스템의 물리적 특성을 규명(identify)할 수 없는 경우에도 그 모형으로 표현되는 추상시스템을 바탕으로 특성화, 예측 내지 제어 목적으로 활용할 수 있다. DDS는 단일변수(univariate)및 다 변수(multivariate) 자료에 모두 적용 가능하며 전달 함수 규명(Transfer Function Identification) 및 닫힘 루우프 시스템(closedloop system)의 모형화 및 해석에도 이용되고 있다.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.12
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• pp.85-98
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• 1998

This paper proposes a new design method of neuro-FLC by the Lamarckian co-adaptation scheme that incorporates the backpropagation learning into the GA evolution in an attempt to find optimal design parameters (fuzzy rule base and membership functions) of application-specific FLC. The design parameters are determined by evolution and learning in a way that the evolution performs the global search and makes inter-FLC parameter adjustments in order to obtain both the optimal rule base having high covering value and small number of useful fuzzy rules and the optimal membership functions having small approximation error and good control performance while the learning performs the local search and makes intra-FLC parameter adjustments by interacting each FLC with its environment. The proposed co-adaptive design method produces better approximation ability because it includes the backpropagation learning in every generation of GA evolution, shows better control performance because the used COG defuzzifier computes the crisp value accurately, and requires small workspace because the optimization procedure of fuzzy rule base and membership functions is performed concurrently by an integrated fitness function on the same fuzzy partition. Simulation results show that the Lamarckian co-adapted FLC produces the most superior one among the differently generated FLCs in all aspects such as the number of fuzzy rules, the approximation ability, and the control performance.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.487-493
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• 1998

Camera calibration is the process of determining the coordinate relationship between a camera image and its real world space. Accurate calibration of a camera is necessary for the applications that involve quantitative measurement of camera images. However, if the camera plane is parallel or near parallel to the calibration board on which 2 dimensional objects are defined(this is called "ill-conditioned"), existing solution procedures are not well applied. In this paper, we propose a neural network-based approach to camera calibration for 2D images formed by a mono-camera or a pair of cameras. Multi-layer perceptrons are developed to transform the coordinates of each image point to the world coordinates. The validity of the approach is tested with data points which cover the whole 2D space concerned. Experimental results for both mono-camera and stereo-camera cases indicate that the proposed approach is comparable to Tsai's method［8］. Especially for the stereo camera case, the approach works better than the Tsai's method as the angle between the camera optical axis and the Z-axis increases. Therefore, we believe the approach could be an alternative solution procedure for the ill -conditioned camera calibration.libration.

• Journal of Korea Multimedia Society
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• v.11 no.3
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• pp.292-300
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• 2008

An algorithm for detecting a line segment in an image is presented using incremental pixel extension. We use a different approach from conventional algorithms, such as the Hough transform approach and the line segment grouping approach. The Canny edge is calculated and an arbitrary point is selected among the edge elements. After the arbitrary point is selected, a base line approximating the line segment is calculated and edge pixels within an arbitrary radius are selected. A weighted value is assigned to each edge pixel, which is selected by using the error of the distance and the direction between the pixel and the base line. A line segment is extracted by Jilting a line using the weighted least square method after determining whether selected pixels are linked or delinked using the sum comparison of the weights. The proposed algorithm is compared with two other methods and results show that our algorithm is faster and can detect the real line segment.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.11
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• pp.87-92
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• 2005

This paper analyzes the performance for an improved multistage parallel interference cancellation (PIC) technique with a reverse-link synchronous transmission technique (RLSTT) for DS-CDMA system in a frequency-selective Rayleigh fading channel with an imperfect power control scheme. The performance degradation due to power control error (PCE), which is approximated by a log-normally distributed random variable, is estimated as a function of the standard deviation of the PCE. The uncoded bit error performance is evaluated in order to estimate the system capacity. Comparing with the conventional one-stage PIC system, we show achievable gain around $60\%$ by the RLSTT even in the presence of PCE. We conclude that the capacity can be further improved via RLSTT, which alleviates the detrimental effects of the PCE

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.4
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• pp.1087-1099
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• 1998

In the content-based image coding, where each object in the scene is encoded independently, the shape, texture and motion information are very important factors. Though the contours representing the shape of an object occupy a great amount of data in proportion to the whole information, they strongly affect the subjective image quaility. Therefore, the distortion of contour coding has to be minimized as much as possible. In this paper, we propose a new method for the contour coding in which the contours are approximated to polygon and the eorror signal occurring from polygonal approximation are transformed with new basis functions. Considering the facts that confour segments occurring from polygonal approximation are smooth curves and error signals have two zero-ending points, we design new basis functions based on the Legendre polynomial and then transform the error signals with them. When applied to synthetic images such as circles, ellipses and etc., the proposed method provides, in overall, outstanding results in respect to the transform coding gain compared with DCT and DST. And in the case when applied to natural images, the proposed method gives better image quality over DCT and comparable results with DST.

• The Journal of the Korea Contents Association
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• v.10 no.5
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• pp.99-106
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• 2010

Multilayer perceptrons(MLPs) or feed-forward neural networks are widely applied to many areas based on their function approximation capabilities. When implementing MLPs for application problems, we should determine various parameters and training methods. In this paper, we discuss the design of MLPs especially for pattern classification problems. This discussion includes how to decide the number of nodes in each layer, how to initialize the weights of MLPs, how to train MLPs among various error functions, the imbalanced data problems, and deep architecture.