• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.4
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• pp.752-757
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• 2006

In the case of the requirement of high speed transmission, OFDM is a powerful technique employed in communications systems suffering from frequency selective fading. In this paper, we apply an optimal adaptive bitloading algorithm technique. The BER performance of the fixed-rate SISO and adaptive SISO is simulated. Specially, we can decompose the MIMO channel into the SISO channel by making use of the singular value decomposition(SVD) assuming channel knowledge in a multipath environment. As a results of simulation, we confirmed that the BER enhancement of MIMO-OFDM system with the bitloadins algorithm was superior to the SISO-OFDM system.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.11
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• pp.1839-1849
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• 1989

An optimal variable assignment algorithm is presented as a decomposition method of MVL functions. A given 3-valued combinational logic function is disintegrated into subfunction composed of the function dependant relation, then extracted implicant output elements from subfunctions are assigned to a T-gates. As a circuit implementation tool, a programmable integarated T-gate module is proposed, and the construction procedure of combinational MVL functions is systematized in each step. This method is expected to give properties of the systematic procedure, possibility of T-gate number reduction, unification of module, and flexibility of module composition. Specially variable decomposition method can be pointed out as an approach to solving the limitation problem of the input and output terminal number in VLSI implementations.

• Smart Structures and Systems
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• v.16 no.5
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• pp.919-935
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• 2015

The Hilbert-Huang transform (HHT) consists of empirical mode decomposition (EMD) and Hilbert spectral analysis. EMD has been successfully applied for identification of mode shapes of structures based on input-output approaches. This paper aims to extend application of EMD for output-only identification of mode shapes of linear structures. In this regard, a new simple and efficient method based on band-pass filtering and EMD is proposed. Having rather accurate estimates of modal frequencies from measured responses, the proposed method is capable to extract the corresponding mode shapes. In order to evaluate the accuracy and performance of the proposed identification method, two case studies are considered. In the first case, the performance of the method is validated through the analysis of simulated responses obtained from an analytical structural model with known dynamical properties. The low-amplitude responses recorded from the UCLA Factor Building during the 2004 Parkfield earthquake are used in the second case to identify the first three mode shapes of the building in three different directions. The results demonstrate the remarkable ability of the proposed method in correct estimation of mode shapes of the linear structures based on rather accurate modal frequencies.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.2 s.95
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• pp.192-198
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• 2005

Empirical mode decomposition(EMD) method has been recently proposed to analyze non-linear and non-stationary data. This method allows the decomposition of one-dimensional signals into intrinsic mode functions(IMFs) and is used to calculate a meaningful multi-component instantaneous frequency. In this paper, it is assumed that each mode of damped vibration signal could be well separated in the form of IMF by EMD. In this case, we can have a new powerful method to calculate natural frequencies and dampings from damped vibration signal which usually has multiple modes. This proposed method has been verified by both simulation and experiment. The results by EMD method whichhas used only output vibration data are almost identical to the results by FRF method which has used both input and output data, thereby proving usefulness and accuracy of the proposed method.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.7
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• pp.501-513
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• 1987

Conditions for achieving noninteraction in nonlinear multivariable systems via the decomposition of state space are well established. The main contribution of this paper is to fully characterize the class of decomposing control laws. The characterization corresponds to a family of simple control laws which are applied to a standard decomposed system(SDS). The SDS is similar to the decomposed systems of Isidori, Krener, Gori-Giorgi, and Monaco but has a finer structure. The finer structure parallels the one used by Gilbert for linear systems. A weaker form of noninteraction, based on input-output behaviour, is decoupling. Some connections between decomposition and decoupling are also established. An example illustrating the importance of the results is given.

• Environmental and Resource Economics Review
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• v.20 no.2
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• pp.255-289
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• 2011

This study made linked Energy IO Table 00-05-08 of 76 sectors in intermediate sectors and analyzed structural decomposition analysis in energy consumption change in industrial sector with both by aggregate data and micro data. Structural decomposition analysis focused value added level change, value added share change of each industry, output structural change of each industry and energy intensity change of each industry as factors. Supply side model based on Ghosh inverse matrix was applied as empirical model because Korea has export driven industrial structure. Empirical results with aggregate data showed that value added change increased energy consumption and output structural change of each industry decreased energy consumption in both 2000~2005 and 2005~2008. However value added share change and energy intensity change caused opposite direction in energy consumption change with time. Policy based on aggregate data can not evaluate effort of each industry in energy efficiency and make effective results because aggregate data delete character of each industry.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.385-390
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• 2011

In this paper, various ultra-wideband (UWB) spatial multiplxing (SM) multiple input multiple output (MIMO) receivers based on a prerake diversity combining scheme are discussed and their performance is analyzed. Several UWB MIMO detection approaches such as zero forcing (ZF), minimum mean square error (MMSE), ordered successive interference cancellation (OSIC), sorted QR decomposition (SQRD), and maximum likelihood (ML) are considered in order to cope with inter-channel interference. The UWB SM systems based on transmitter-side multipath preprocessing and receiver-side MIMO detection can either boost the transmission data rate or offer significant diversity gain and improved BER performance. The error performance and complexity of linear and nonlinear detection algorithms are comparatively studied on a lognormal multipath fading channel.

• Environmental and Resource Economics Review
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• v.9 no.3
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• pp.489-513
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• 2000

This paper introduces a new method to estimate and decompose sources of carbon dioxide emissions using an input-output model with decomposition method free of residual usually associated with this kind of analysis. This method is different from others, using what we call 'mean rate-of-change index (MRCI)' for weights of the decomposed terms. Ang et al.(1998) asserted that logarithmic mean divisia index(LMDI) is superior to Laspeyres index(LI) or simple average divisia index(SADI) since it reduces residual to zero. We claim that our method is an improvement over the other methods because it enables residual free decomposition even when data contain negative values, the case which LMDI cannot handle. We demonstrate by way of showing some examples that our method is superior to LI, SADI(Proops, 1993 and Chung, 1998) or LMDI(Ang et al., 1998).

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.133-138
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• 2006

Singular value decomposition (SDV) approach is applied to the observability analysis of GPS/INS in this paper. A measure of observability for a subspace is introduced. It indicates the minimum size of perturbation in the information matrix that makes the subspace unobservable. It is shown that the measure has direct connections with observability of systems, error covariance, and singular structure of the information matrix. The observability measure given in this paper is applicable to the multi-input/multi-output time-varying systems. An example on the observability analysis of GPS/INS is given. The measure of observability is confirmed to be less sensitive to system model perturbation. It is also shown that the estimation error for the vertical component of gyro bias can be considered unobservable for small initial error covariance for a constant velocity horizontal motion.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1C
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• pp.43-50
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• 2007

In the paper, we address QRM-MLD (Maximum Likelihood Detection with QR Decomposition and M-algorithm) signal detection method for spatially multiplexed MIMO (Multiple Input Multiple Output) systems. Recently, the QRM-MLD signal detection method which can achieve 1Gbps transmission speed for next generation mobile communication was implemented in a MIMO testbed for the mobile moving at a pedestrian speed. In the paper, we propose a novel signal detection method 'reduced complexity QRM-MLD' that achieves identical error performance as the QRM-MLD while reducing the computational complexity significantly. We rigorously compare the two detection methods in terms of computational complexity to show the complexity reduction of the proposed method. We also perform a set of computer simulations to demonstrate that two detection methods achieve identical error performance.