• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.93-101
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• 2007

To jointly optimize the spatial registration and the exposure compensation, an iterative registration algorithm, the Lucas-Kanade algorithm, is combined with an exposure compensation algorithm, which is based on the histogram transformation function. Based on a simple regression model, a nonparametric estimator, the empirical conditional mean, and its polynomial fitting are used as histogram transformation functions for the exposure compensation. Since the proposed algorithm is composed of separable optimization phases, the proposed algorithm is more advantageous than the joint approaches of Mann and Candocia in the aspect of implementation flexibility. The proposed algorithm performs a better registration for real images than the case of registration that does not consider the exposure difference.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.10
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• pp.853-861
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• 2012

This paper considers one of the explicit guidance algorithms, which has been proposed by Jaggers, to determine the closed-loop guidance algorithm for upper stages of a 3-staged space launch vehicle. Its commanded thrust vector is closer to the optimal solution when compared with that obtained by using the well-known Powered Explicit Guidance (PEG), which has been developed through the Space Shuttle program. Its performance is evaluated here by applying for guidance of the launcher during the second and third stages. Furthermore, to generate more precise guidance commands, it is attempted not to use the approximate formulas for the derivation of the original guidance law, and it is shown that performance is improved in comparison with the original.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.3
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• pp.17-30
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• 2000

In this paper, we propose an efficient algorithm to produce 3-D surface model from a set of range data, based on NURBS (Non-Uniform Rational B-Splines) surface fitting technique. It is assumed that the range data is initially unorganized and scattered 3-D points, while their connectivity is also unknown. The proposed algorithm consists of three steps: initial model approximation, hierarchical representation, and construction of the NURBS patch network. The mitral model is approximated by polyhedral and triangular model using K-means clustering technique Then, the initial model is represented by hierarchically decomposed tree structure. Based on this, $G^1$ continuous NURBS patch network is constructed efficiently. The computational complexity as well as the modeling error is much reduced by means of hierarchical decomposition and precise approximation of the NURBS control mesh Experimental results show that the initial model as well as the NURBS patch network are constructed automatically, while the modeling error is observed to be negligible.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2298-2304
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• 2015

In this paper, we provide a new approach which optimizes the vertical tilting angle of the base station for multi-cell multiple-input single-output (MISO) downlink active antenna systems (AAS). Instead of the conventional optimal algorithm which requires an exhaustive search, we propose simple and near optimal algorithms. First, we represent a large system approximation based vertical beamforming algorithm which is applied to the average sum rate by using the random matrix theory. Next, we suggest a signal-to-leakage-and-noise ratio (SLNR) based vertical beamforming algorithm which simplifies the optimization problem considerably. In the simulation results, we demonstrate that the performance of the proposed algorithms is near close to the exhaustive search algorithm with substantially reduced complexity.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.10
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• pp.1012-1015
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• 2011

The decision-directed blind equalization algorithm is often used due to its simplicity and good convergence property when the eye pattern is open. However, in a channel where the eye pattern is closed, the decision-directed algorithm is not guaranteed to converge. Hence, a modified Bussgang-type algorithm using a hyperbolic tangent function for zero-memory nonlinear(ZNL) function has been proposed and applied to avoid this problem by Filho et al. But application of this algorithm includes the calculation of hyperbolic tangent function and its derivative or a look-up table which may need a large amount of memory due to channel variations. To reduce the computational and/or hardware complexity of Filho's algorithm, in this paper, an improved method for the decision-directed algorithm is proposed. In the proposed scheme, the ZNL function and its derivative are respectively set to be the original signum function and a narrow rectangular pulse which is an approximation of Dirac delta function. It is shown that the proposed scheme, when it is combined with decision-directed algorithm, reduces the computational complexity drastically while it retains the convergence and steady-state performance of the Filho's algorithm.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.1
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• pp.82-88
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• 2008

In this paper, Runge-Kutta (RK)-Butcher algorithm is proposed to study the periodic and oscillatory problems. Simulation results obtained using RK-Butcher algorithms and the classical fourth order Runge-Kutta (RK(4)) methods are compared with the exact solutions of a few periodic and oscillatory problems to confirm the performance of the proposed algorithm. The simulation results from RK-Butcher algorithms are always found to be very close to the exact solutions of these problems. Further, it is found that the RK-Butcher algorithm is superior when compared to RK(4) methods in terms of accuracy. The RK-Butcher algorithm can be easily implemented in a programming language and a more accurate solution may be obtained for any length of time. RK-Butcher algorithm is applicable as a good numerical algorithm for studying the problems of orbit and two body as it gives the nearly identical solutions.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2052-2054
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• 2003

본 논문에서는 혼돈 비선형 시스템의 지능 제어를 위해 간접 적응 제어 기법에 기반한 웨이블릿 신경 회로망 제어기 설계 방법을 제안한다. 제어기 성능에 큰 영향을 미칠 수 있는 웨이블릿 신경 회로망 구조의 파라미터 동정은 본질적으로 강인하고 전역 최적해에 근사한 값을 결정할 수 있는 유전 알고리듬을 사용한다. 본 논문에서 제안한 제어 방법은 유전 알고리듬을 이용한 혼돈 비선형 시스템의 오프라인 동정 모델 및 기준 신호와 플랜트 출력으로 정의되는 제어 오차를 이용하여 원하는 제어 입력을 생성한다. 한편 본 논문에서 제안한 웨이블릿 신경 회로망 제어기를 대표적인 연속 시간 혼돈 비선형 시스템인 Duffing 시스템에 적용하여 설계된 제어기의 효율성 및 우수성을 검증하고자 한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.10B
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• pp.1382-1389
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• 2001

움직임 보상-이산 코사인 변환 (motion compensation-discrete cosine transform : MC-DCT) 기반의 동영상 부호화 기법이 부호화 효율성 및 구현의 단순성으로 인해 널리 사용되고 있으나, 에러 환경에서 구조적으로 취약한 면이 있다. 본 논문에서는 다중 메모리 움직임 보상 예측 (long-term memory motion compensated prediction : LTMP) 기반의 다중 레프런스 프레임을 사용하여 에러에 강인한 동영상 부호화 기법을 제안한다. 또한 제안하는 알고리듬에 기반한 에러 은닉 기법 (error concealment : EC)을 구현한다. 즉, R-D (rate-distortion) 최적화에 프레임간 움직임 벡터 (temporal motion vectors)의 확산 인자를 추가하여 에러에 대한 강인성 및 에러 은닉 기법의 효율성을 증가시켰다. 또한, 제안하는 알고리듬은 시간축상의 에러 전파를 피드백 정보 (negative acknowledgement : NAK)를 사용하여 억제한다. 즉, NAK는 채널 에러에 의해 손실된 영역과 에러가 전파된 영역을 추정하여 움직임 보상 영역에서 제외되도록 하는데 이용된다. 따라서, 제안하는 알고리듬은 PSNR 측면에서 FIU (forced intra update)에 근사하는 성능을 보이나, FIU와는 달리 비트율의 증가를 피할 수 있어 제한된 대역폭의 네트웍을 효율적으로 사용할 수 있다. 컴퓨터 모의 실험을 통해 제안하는 알고리듬이 기존의 H.263 및 LTMP 기반의 부호기에 비해 에러 환경에서 주관적 및 객관적 화질 측면에서 성능이 우수함을 보인다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.1
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• pp.33-41
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• 2002

In this paper, we present a frequency weighted model reduction using LMIs for minimizing the H$\infty$ weighted model error compared with the methods of frequency weighted balanced truncation and frequency weighted Hankel norm approximation. The proposed algorithm, its form is equal to the sufficient condition of performance preserving controller approximation, is based on an iterative two-step LMI scheme induced from bound real lemma. So, it can be applied to the problem of the performance preserving controller approximation. The controller reduction is useful in a practical control design and ensures its easy implementation and high reliability The validity of the proposed algorithm is shown through numerical examples. Additionaly, we extend the proposed algorithm to performance preserving controller approximation by applying to the HIMAT(highly maneuverable aircraft technology) system.

• Journal of IKEEE
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• v.14 no.3
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• pp.182-189
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• 2010

A new Adaptive neural state-feedback controller for the fully nonaffine pure-feedback nonlinear system are presented in this paper. By reformulating the original pure-feedback system to a standard normal form with respect to newly defined state variables, the proposed controller requires no backstepping design procedure. Avoiding backstepping makes the controller structure and stability analysis considerably simple. The proposed controller employs only one neural network to approximate unknown ideal controllers, which highlights the simplicity of the proposed neural controller. Simulation examples demonstrate the efficiency and performance of the proposed approach.