• 한국정보통신학회논문지
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• 제9권6호
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• pp.1167-1173
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• 2005

본 논문에서는 DS-CDMA 신호들의 코드 타이밍을 획득하기 위하여 안테나 어레이의 이용에 관한 내용을 다루고자 한다. 다중 사용자 환경의 시변 Rayleigh 페이딩 채널 하에서 다중의 고정 빔들을 기존의 MUSIC 동기 획득 방법에 적용함으로서 동기 획득 확률들을 평가한다. 전 방위각 영역을 공간 필터링을 위해서 안테나의 수만큼 나누어서 각각의 고정 빔이 각 방위각 구역을 맡도록 한다. 간섭 신호 억제 능력을 가진 고정 빔들은 부가적인 자유도를 제공한다. 그리하여 단 하나의 안테나를 사용하는 기존의 MUSIC 알고리즘보다 더 많은 사용자들의 동기 획득을 위해서 다중 빔 기반의 MUSIC 추정기를 사용할 수 있도록 한다. 이러한 다중 빔 기반의 부분공간 접근 방법을 다중 사용자 시나리오에서 단 하나의 안테나를 사용하는 MUSIC 기법의 성능을 상당히 개선할 수 있음을 검증하기 위해서 시뮬레이션을 수행한다.

• International Journal of Control, Automation, and Systems
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• 제5권4호
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• pp.397-409
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• 2007

In this paper, we propose a nonlinear guidance law for missiles against maneuvering targets. First, we derive the equations of motion described in the line-of-sight reference frame and then we define the equilibrium subspace of the nonlinear system to guarantee target interception within a finite time. Using Sontag's formula, we derive a nonlinear guidance law that always delivers the state to the equilibrium subspace. If the speed of the missile is greater than that of the target, the proposed law has global capturability in that, under any initial launch conditions, the missile can intercept the maneuvering target. The proposed law also minimizes the integral cost of the control energy and the weighted square of the state. The performance of the proposed law is compared with the augmented proportional navigation guidance law by means of numerical simulations of various initial conditions and target maneuvers.

• Wind and Structures
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• 제21권6호
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• pp.677-691
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• 2015

In this study, the geometrical setup of a turbine blade is tracked. A research-scale rotating turbine blade system is setup with a single 3-axes accelerometer mounted on one of the blades. The turbine system is rotated by a controlled motor. The tilt and rolling angles of the rotating blade under operating conditions are determined from the response measurement of the single accelerometer. Data acquisition is achieved using a prototype wireless sensing system. First, the Rodrigues' rotation formula and an optimization algorithm are used to track the blade rolling angle and pitching angles of the turbine blade system. In addition, the blade flapwise natural frequency is identified by removing the rotation-related response induced by gravity and centrifuge force. To verify the result of calculations, a covariance-driven stochastic subspace identification method (SSI-COV) is applied to the vibration measurements of the blades to determine the system natural frequencies. It is thus proven that by using a single sensor and through a series of coordinate transformations and the Rodrigues' rotation formula, the geometrical setup of the blade can be tracked and the blade flapwise vibration frequency can be determined successfully.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권5호
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• pp.2141-2155
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• 2020

In order to meet the requirements of background change, illumination variation, moving shadow interference and high accuracy in object detection of moving camera, and strive for real-time and high efficiency, this paper presents an object detection algorithm based on sparse approximation recursion and sparse coding migration in subspace. First, low-rank sparse decomposition is used to reduce the dimension of the data. Combining with dictionary sparse representation, the computational model is established by the recursive formula of sparse approximation with the video sequences taken as subspace sets. And the moving object is calculated by the background difference method, which effectively reduces the computational complexity and running time. According to the idea of sparse coding migration, the above operations are carried out in the down-sampling space to further reduce the requirements of computational complexity and memory storage, and this will be adapt to multi-scale target objects and overcome the impact of large anomaly areas. Finally, experiments are carried out on VDAO datasets containing 59 sets of videos. The experimental results show that the algorithm can detect moving object effectively in the moving camera with uniform speed, not only in terms of low computational complexity but also in terms of low storage requirements, so that our proposed algorithm is suitable for detection systems with high real-time requirements.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.357-357
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• 2000

In this study, we consider a multi-input multi-output styrene polymerization reactor system for which the monomer conversion and the weight average molecular weight are controlled by manipulating the jacket inlet temperature and the feed flow rate. The reactor system is identified by using a linear subspace identification method and then the output feedback model predictive controller is constructed on the basis of the identified model. Here we use the Best Linear Unbiased Estimation (BLUE) filter as a stochastic estimator instead of the Kalman filter. The BLUE filter observes the state successfully without any a priori information of initial states. In contrast to the Kalman filter, the BLUE filter eliminates the offset by observing the state of the augmented system regardless of a priori information of the initial state for an integral white noise augmented system. A BLUE filter has a finite impulse response (FIR) structure which utilizes finite measurements and inputs on the most recent time interval [i-N, i] in order to avoid long processing times.

• 대한수학회보
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• 제59권2호
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• pp.285-301
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• 2022

In this paper, we mainly study the random sampling and reconstruction of signals living in the subspace V^p(𝚽, 𝚲) of L^p(ℝ^d), which is generated by a family of molecules 𝚽 located on a relatively separated subset 𝚲 ⊂ ℝ^d. The space V^p(𝚽, 𝚲) is used to model signals with finite rate of innovation, such as stream of pulses in GPS applications, cellular radio and ultra wide-band communication. The sampling set is independently and randomly drawn from a general probability distribution over ℝ^d. Under some proper conditions for the generators 𝚽 = {𝜙_λ : λ ∈ 𝚲} and the probability density function 𝜌, we first approximate V^p(𝚽, 𝚲) by a finite dimensional subspace V^p_N (𝚽, 𝚲) on any bounded domains. Then, we prove that the random sampling stability holds with high probability for all signals in V^p(𝚽, 𝚲) whose energy concentrate on a cube when the sampling size is large enough. Finally, a reconstruction algorithm based on random samples is given for signals in V^p_N (𝚽, 𝚲).

• 대한원격탐사학회지
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• 제33권5_1호
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• pp.547-557
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• 2017

본 연구에서는 탐지하고자 하는 표적신호를 초기 엔드멤버로 하여 Iterative Error Analysis를 통해 배경물질들의 반사 스펙트럼을 순차적으로 엔드멤버로 추출하고, 추출된 엔드멤버들을 이용하여 분광 혼합분석함으로써 표적물질의 분포를 탐지하는 새로운 초분광 표적탐지 기법을 제안한다. 제안된 기법에서는 표적물질에 대한 점유율의 변화가 주어진 문턱값보다 작아질 때 엔드멤버 추출을 위한 반복을 멈추게 된다. 이 기법은 Orthogonal Subspace Projection과 같은 모델 기반 표적 탐지기법들과 달리 사전에 엔드멤버들을 확보해야 할 필요가 없으며, Matched Filter와 같은 확률론적 표적 탐지 기법들과 달리 배경 전체를 하나의 신호로 특징화하지 않기 때문에 표적의 희소성 여부에 의한 영향을 받지 않는다는 장점을 가지고 있다. 실제 항공 초분광 영상자료 및 다양한 인공 표적물질들이 삽입된 모의 초분광 영상자료를 이용한 실험 결과, 제안된 방법이 희소 및 비 희소 표적의 탐지에 매우 효과적임이 확인되었다. 제안된 방법은 표적 물체 탐지뿐만 아니라 광물, 오염물질 등 자원 및 환경 분야에서 다양한 피복 물질을 탐지하는데 효과적으로 사용될 수 있을 것으로 기대된다.

• Journal of Electrical Engineering and Technology
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• 제10권5호
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• pp.2179-2188
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• 2015

Recently, many researches have been done to solve the challenging problem of Blind Source Separation (BSS) problems in the underdetermined cases, and the “Two-step” method is widely used, which estimates the mixing matrix first and then extracts the sources. To estimate the mixing matrix, conventional algorithms such as Single-Source-Points (SSPs) detection only exploits the sparsity of original signals. This paper proposes a new underdetermined mixing matrix estimation method for time-delayed mixtures based on the receiver prior exploitation. The prior information is extracted from the specific structure of the complex-valued mixing matrix, which is used to derive a special criterion to determine the SSPs. Moreover, after selecting the SSPs, Agglomerative Hierarchical Clustering (AHC) is used to automaticly cluster, suppress, and estimate all the elements of mixing matrix. Finally, a convex-model based subspace method is applied for signal separation. Simulation results show that the proposed algorithm can estimate the mixing matrix and extract the original source signals with higher accuracy especially in low SNR environments, and does not need the number of sources before hand, which is more reliable in the real non-cooperative environment.

• 전기학회논문지
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• 제59권2호
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• pp.436-444
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• 2010

In this study, we introduce and discuss a concept of a granular-oriented radial basis function neural networks (GRBF NNs). In contrast to the typical architectures encountered in radial basis function neural networks(RBF NNs), our main objective is to develop a design strategy of GRBF NNs as follows : (a) The architecture of the network is fully reflective of the structure encountered in the training data which are granulated with the aid of clustering techniques. More specifically, the output space is granulated with use of K-Means clustering while the information granules in the multidimensional input space are formed by using a so-called context-based Fuzzy C-Means which takes into account the structure being already formed in the output space, (b) The innovative development facet of the network involves a dynamic reduction of dimensionality of the input space in which the information granules are formed in the subspace of the overall input space which is formed by selecting a suitable subset of input variables so that the this subspace retains the structure of the entire space. As this search is of combinatorial character, we use the technique of genetic optimization to determine the optimal input subspaces. A series of numeric studies exploiting some nonlinear process data and a dataset coming from the machine learning repository provide a detailed insight into the nature of the algorithm and its parameters as well as offer some comparative analysis.

• Journal of applied mathematics & informatics
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• 제8권2호
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• pp.305-326
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• 2001

We introduce a class of multilevel recursive incomplete LU preconditioning techniques (RILUM) for solving general sparse matrices. This techniques is based on a recursive two by two block incomplete LU factorization on the coefficient martix. The coarse level system is constructed as an (approximate) Schur complement. A dynamic preconditioner is obtained by solving the Schur complement matrix approximately. The novelty of the proposed techniques is to solve the Schur complement matrix by a preconditioned Krylov subspace method. Such a reduction process is repeated to yield a multilevel recursive preconditioner.