• Journal of information and communication convergence engineering
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• v.13 no.4
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• pp.241-247
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• 2015

Cognitive radio has been attracting increased attention as an effective approach to improving spectrum efficiency. One component of cognitive radio, spectrum sensing, has an important relationship with the performance of cognitive radio. In this paper, after a summary and analysis of the existing spectrum-sensing algorithms, we report that the existing eigenvalue-based semi-blind detection algorithm and blind detection algorithm have not made full use of the eigenvalues of the received signals. Applying multi-antenna systems to cognitive users, we design a variety of spectrum-sensing algorithms based on the joint distribution of the eigenvalues of the received signal. Simulation results validate that the proposed algorithms in this paper are able to detect whether the signal of the primary user exists or not with high probability of detection in an environment with a low signal-to-noise ratio. Compared with traditional algorithms, the new algorithms have the advantages of high detection performance and strong robustness

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.1
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• pp.41-46
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• 2010

In this paper, the DoA(Direction of Arrival) estimator using unitary MUSIC algorithm is studied. The complex-valued correlation matrix of MUSIC algorithm is transformed to the real-valued one using unitary transform for easy implementation. The eigenvalue and eigenvector are obtained by the combined Jacobi-CORDIC algorithm. CORDIC algorithm can be implemented by only ADD and SHIFT operations and MUSIC spectrum computed by 256 point DFT algorithm. Results of unitary MUSIC algorithm designed by System Generator for FPGA implementation is entirely consistent with Matlab results. Its performance is evaluated through hardware co-simulation and resource estimation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.6A
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• pp.480-487
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• 2012

In multicarrier code-division multiple access (MC-CDMA) systems, conventional blind channel estimation schemes require the inverse matrix calculation or eigenvalue decomposition of the received signal covariance matrix. Therefore, computational complexity of the conventional schemes is too high and they cannot be employed in downlink systems. In this paper, we propose a simple blind channel estimation scheme with very low computational complexity. Simulation results show that the proposed scheme has better channel estimation and bit error rate (BER) performance than the conventional schemes.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1017-1030
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• 2016

This study focuses on the system identification of reinforced concrete bridges using vector autoregressive model (VAR). First, the time series output response from a bridge establishes the autoregressive (AR) models. AR models are one of the most accurate methods for stationary time series. Burg's algorithm estimates the autoregressive coefficients (ARCs) at p-lag by reducing the sum of the forward and the backward errors. The computed ARCs are assembled in the state system matrix and the eigen-system realization algorithm (ERA) computes: the eigenvector matrix that contains the vectors of the mode shapes, and the eigenvalue matrix that contains the associated natural frequencies. By taking advantage of the characteristic of the AR model with ERA (ARMERA), civil engineering can address problems related to damage detection. Operational modal analysis using ARMERA is applied to three experiments. One experiment is coupled with an artificial neural network algorithm and it can detect damage locations and extension. The neural network uses a specific number of ARCs as input and multiple submatrix scaling factors of the structural stiffness matrix as output to represent the damage.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.868-876
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• 2016

MUSIC (multiple signal classification) algorithm is a representative algorithm estimating the angle of arrival using the eigenvalues and eigenvectors. Generally, the eigenvalues and eigenvectors are obtained through the eigen-analysis, but this analysis requires high computational complexity and late convergence time. For this reason, it is almost impossible to construct the real-time system with low-cost using this approach. Even though QR iteration is considered as the eigen-analysis approach to improve these problems, this is inappropriate to apply to the MUSIC algorithm. In this paper, we analyze the problems of conventional method based on the eigenvalues for convergence decision and propose the improved decision algorithm using the eigenvectors.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.8
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• pp.693-700
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• 2008

The primary mirror system in a satellite camera is an opto-mechanically coupled system for a reason that optical and mechanical behaviors are intricately interactive. In order to enhance the opto-mechanical performance of the primary mirror system, opto-mechanical behaviors should be thoroughly investigated by using various analysis procedures such as elastic, thermo-elastic, optical and eigenvalue analysis. In this paper, optimal design of the bipod flexure mounts for high opto-mechanical performance is performed. Optomechanical performances considered in this paper are RMS wavefront error under the gravity and thermal loading conditions and 1st natural frequency of the mirror system. The procedures of the flexure mounts design based on design of experiments and statistics is as follows. The experiments for opto-mechanical analysis are constructed based on the tables of orthogonal arrays and analysis of each experiment is carried out. In order to deal with the multiple opto-mechanical properties, MADM (Multiple-attribute decision making) is employed. From the analysis results, the critical design variables of the flexure mounts which have dominant influences on opto-mechanical performance are determined through analysis of variance and F-test. The regression model in terms of the critical design variables is constructed based on the response surfaceanalysis. Then the critical design variables are optimized from the regression model by using SQP algorithm. Opto-mechanical performance of the optimal bipod flexure mounts is verified through analysis.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.1
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• pp.15-23
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• 2003

This paper proposes a fast direction of arrival (DOA) estimation algorithm that can rapidly estimate incidence angles of incoming signals using a pseudo covariance matrix. The conventional subspace DOA estimation methods such as MUSIC (multiple signal classification) algorithms need many sample signals to acquire covariance matrix of input signals. Thus, it is difficult to estimate the DOAs of signals because they cannot perform DOA estimation during receiving sample signals. Also if the D0As of signals are changing rapidly, conventional algorithms cannot estimate incidence angles of signals exactly. The proposed algorithm obtains bearing response and directional spectrum after acquiring pseudo covariance matrix of each snapshot. The incidence angles can be exactly estimated by using the bearing response and directional spectrum. The proposed DOA estimation algorithm uses only concurrent snapshot so as to obtain covariance matrix. Compared to conventional DOA estimation methods. The proposed algorithm has an advantage that can estimate DOA of signal rapidly.

• Structural Engineering and Mechanics
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• v.27 no.5
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• pp.625-638
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• 2007

The damage detection process may appear difficult to be implemented for truss structures because not all degrees of freedom in the numerical model can be experimentally measured. In this context, the damage locating vector (DLV) method, introduced by Bernal (2002), is a useful approach because it is effective when operating with an arbitrary number of sensors, a truncated modal basis and multiple damage scenarios, while keeping the calculation in a low level. In addition, the present paper also evaluates the noise influence on the accuracy of the DLV method. In order to verify the DLV behavior under different damages intensities and, mainly, in presence of measurement noise, a parametric study had been carried out. Different excitations as well as damage scenarios are numerically tested in a continuous Warren truss structure subjected to five noise levels with a set of limited measurement sensors. Besides this, it is proposed another way to determine the damage locating vectors in the DLV procedure. The idea is to contribute with an alternative option to solve the problem with a more widespread algebraic method. The original formulation via singular value decomposition (SVD) is replaced by a common solution of an eigenvector-eigenvalue problem. The final results show that the DLV method, enhanced with the alternative solution proposed in this paper, was able to correctly locate the damaged bars, using an output-only system identification procedure, even considering small intensities of damage and moderate noise levels.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2003.05a
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• pp.87-91
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• 2003

It has well known that MUSIC and ESPRIT algorithms estimate angle of arrival(AOA) with high resolution by eigenvalue decomposition of the covariance matrix which were obtained from the array antennas. However, the disadvantage of MUSIC and ESPRIT is that they are computationally ineffective, and then they are difficult to implement in real time. The other problem of MUSIC and ESRPIT is to require calibrated antennas with uniform features, and are sensitive to the manufacturing facult and other physical uncertainties. To overcome these disadvantages, several method using neural model have been study. For multiple signals, those require huge training data prior to AOA estimation. This paper proposes the algorithm for AOA estimation by interconnected hopfield neural model. Computer simulations show the validity of the proposed algorithm. The proposed method does not require huge training procedure and only assigns interconnected coefficients to the neural network prior to AOA estimation.

• Journal of Navigation and Port Research
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• v.27 no.4
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• pp.465-469
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• 2003

It has well known that MUSIC and ESPRIT algorithms estimate angle of arrival(AOA) with high resolution by eigenvalue decomposition of the covariance matrix which were obtained from the array antennas, However, the disadvantage of MUSIC and ESPRIT is that they are computationally ineffective, and then they are difficult to implement in real time. the other problem of MUSIC and ESPRIT is to require calibrated antennas with uniform features, and are sensitive ti the manufacturing fault and other physical uncertainties. To overcome these disadvantages, several method using neural model have been study. For multiple signals, those methods require huge training data prior to AOA estimation. This paper proposes the algorithm for AOA estimation by interconnected Hopfield neural model. Computer simulations show the validity of the proposed algorithm. It follows that the proposed method yields better AOA estimates than MUSIC. Moreover, out method does not require huge training procedure and only assigns interconnected coefficients to the neural network prior to AOA estimation.