• ETRI Journal
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• v.34 no.4
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• pp.511-517
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• 2012

The best linear unbiased estimator (BLUE) is most suitable for practical application and can be determined with knowledge of only the first and second moments of the probability density function. Although the BLUE is an existing algorithm, it is still largely unexplored and has not yet been applied to channel estimation in amplify and forward (AF)-based wireless relay networks (WRNs). In this paper, a BLUE-based algorithm is proposed to estimate the overall channel impulse response between the source and destination of AF strategy-based WRNs. Theoretical mean square error (MSE) performance for the BLUE is derived to show the accuracy of the proposed channel estimation algorithm. In addition, the Cram$\acute{e}$r-Rao lower bound (CRLB) is derived to validate the MSE performance. The proposed BLUE channel estimation algorithm approaches the CRLB as the length of the training sequence and number of relays increases. Further, the BLUE performs better than the linear minimum MSE estimator due to the minimum variance characteristic exhibited by the BLUE, which happens to be a function of signal-to-noise ratio.

• The Journal of the Acoustical Society of Korea
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• v.20 no.8
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• pp.58-66
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• 2001

In this paper, a computationally efficient time delay and doppler estimation algorithm is proposed for active sonar with Linear Frequency Modulated (LFM) signal. To reduce the computational burden of the conventional estimation algorithm, an algebraic equation is used which represents the relationship between the time delay and doppler in cross-ambiguity function of the LFM signal. The algebraic equation is derived based on the Fast maximum Likelihood (FML) method. Using this algebraic relation, the time delay and doppler are estimated with two 1-D search instead of the conventional 2-D search. The estimation errors of the proposed algorithm are analyzed for various SNR's. The simulation result demonstrates the good performance of the proposed algorithm.

• Journal of Broadcast Engineering
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• v.15 no.3
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• pp.355-361
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• 2010

Video Compression is the key technology for the transmission of multi-media data. Because the Motion Estimation is the most complex module in the video compression, fast motion estimation algorithm is essential for the real-time application. In this paper, we propose an enhanced binary motion estimation algorithm based on the wavelet transform. Proposed algorithm improve the quality of coded video.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.2
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• pp.146-156
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• 1998

Thispapr proposes hybrid navigation parameter estimation using sequential aerial images. The proposed navigation parameter estimation system is composed of two parts: relative position estimation and absolute position estimation. the relative position estimation recursively computes the current velocity and absolute position estimation. The relative position estimation recursively computes the current velocity and position of an aircraft by accumulating navigation parameters extracted from two succesive aerial images. Simple accumulation of parameter values decreases reliability of the extracted parameters as an aircraft goes on navigating. therefore absolute position estimation is required to compensate for position error generated in the relative position step. The absolute position estimation algorithm combining image matching and digital elevation model(DEM) matching is presented. Computer simulation with real aerial image sequences shows the efficiency of the proposed hybrial algorithm.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.3
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• pp.289-295
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• 2013

It is important to know exact values of Interior Permanent Magnet Synchronous Motors(IPMSM)' parameters such as stator resistance and inductance in order to have their high performance. This paper proposes a novel motor parameter(stator resistance, d&q axis inductance) estimation algorithm for IPMSM. The proposed estimation method utilizes back-EMF equations and model reference adaptive system(MRAS). The algorithm using back-EMF estimates d and q axis inductances in the constant torque region, and the stator resistance is estimated by using MRAS with the estimated inductance regardless of speed regions. The validity of the proposed algorithm is verified by simulations and experiments.

• Journal of information and communication convergence engineering
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• v.12 no.4
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• pp.215-220
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• 2014

We consider quantization optimized for distributed estimation, where a set of sensors at different sites collect measurements on the parameter of interest, quantize them, and transmit the quantized data to a fusion node, which then estimates the parameter. Here, we propose an iterative quantizer design algorithm with a weighted distance rule that allows us to reduce a system-wide metric such as the estimation error by constructing quantization partitions with their optimal weights. We show that the search for the weights, the most expensive computational step in the algorithm, can be conducted in a sequential manner without deviating from convergence, leading to a significant reduction in design complexity. Our experments demonstrate that the proposed algorithm achieves improved performance over traditional quantizer designs. The benefit of the proposed technique is further illustrated by the experiments providing similar estimation performance with much lower complexity as compared to the recently published novel algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2446-2462
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• 2016

In this paper, a frequency domain Expectation-Maximization (EM)-based channel estimation algorithm for Space Time Block Coded-Orthogonal Frequency Division Multiplexing (STBC-OFDM) systems is investigated to support higher data rate applications in wireless communications. The computational complexity of the frequency domain EM-based channel estimation is increased when higher order constellations are used because of the ascending size of the search set space. Thus, a search set reduction algorithm is proposed to decrease the complexity without sacrificing the system performance. The performance results of the proposed algorithm is obtained in terms of Bit Error Rate (BER) and Mean Square Error (MSE) for 16QAM and 64QAM modulation schemes.

• Journal of Electrical Engineering and Technology
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• v.6 no.4
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• pp.459-465
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• 2011

A phasor estimation algorithm based on the least square curve fitting technique for the distorted secondary current due to current transformer (CT) saturation is proposed. The mathematical form of the secondary current during CT saturation is represented as the scaled primary current with magnetizing current. The information on the scaled primary current is estimated using the least square technique, with the measured secondary current in the saturated section. The proposed method can estimate the phasor of a fundamental frequency component during the saturated period. The performance of the algorithm is validated under various fault and CT conditions using a C400 CT model. A series of performance evaluations shows that the proposed phasor estimation algorithm can estimate the phasor of the fundamental frequency component with high accuracy, regardless of fault conditions and CT characteristics.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.173-175
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• 2013

In this paper, we propose a fast and low-complexity Motion Estimation (ME) algorithm for High Efficiency Video Coding (HEVC). Motion estimation occupies 77~81% of the amount of computation in HEVC. After all, the main key of codec implementation is to find a fast and low-complexity motion estimation algorithm and architecture. The proposed algorithm uses only 1% of the amount of operations compared to full search algorithm while maintaining compression performance with slight loss of 0.6% (BDBR).

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.416-418
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• 2006

In this paper, a new acoustic echo cancellation approach based on the DUET algorithm and scaling factor estimation is proposed to solve the scaling ambiguity in case of blind separation based acoustic echo cancellation in a noisy environment. In hands-free full-duplex communication system. acoustic noises picked up by the microphone are mixed with echo signal. For this reason, the echo cancellation system may provide poor performance. For that purpose, a degenerate unmixing estimation technique, adjusted in the time-frequency domain, is employed to separate undesired echo signals and noises. Also, since scaling and permutation ambiguities have not been solved in the blind source separation algorithm, kurtosis for the desired signal selection and a scaling factor estimation algorithm are utilized in this rarer for the separation of an echo signal. Simulation results demonstrate that the proposed approach yields better echo cancellation and noise reduction performances, compared with conventional methods.