• Journal of Power Electronics
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• v.14 no.5
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• pp.1057-1068
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• 2014

Phase-locked loops (PLL) based on the synchronous reference frame (SRF-PLL) have recently become the most widely-used for grid synchronization in three phase grid-connected inverters. However, it is difficult to study their performance since they are nonlinear systems. To estimate the performances of a SRF-PLL, a canonical small-signal linearized model has been developed in this paper. Based on the proposed model, several significant specifications of a SRF-PLL, such as the capture time, capture rang, bandwidth, the product of capture time and bandwidth, and steady-state error have been investigated. Finally, a noise model of a SRF-PLL has been put forward to analyze the noise rejection ability by computing the SNR (signal-to-noise ratio) of a SRF-PLL. Several simulation and experimental results have been provided to verify and validate the obtained conclusions. Although the proposed model and analysis method are based on a SRF-PLL, they are also suitable for analyzing other types of PLLs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.3A
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• pp.119-128
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• 2003

A space diversity technique was applied to the conventional optimal beamforming structure using antenna arrays at the base station receiver in the wireless mobile communication system to get performance enhancement due to interference rejection and fading resistance ability of it. To demonstrate the benefit of proposed system, we derived output signal to interference plus noise ratio (SINR) of combined signal from all sub-array groups considering the fading effects and compared with the beamforming-only system. From the analysis and simulation results, we showed that the proposed system can provide high performance gain under Rayleigh fading channel.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.7
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• pp.711-719
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• 2010

Heliostat, as a concentrator reflecting the incident solar energy to the receiver located at the tower, is the most important system in the tower-type solar thermal power plant, since it determines the efficiency and performance of solar thermal plower plant. Thus, a good sun tracking ability as well as its good optical property are required. In this paper, we propose a method to compensate the heliostat sun tracking error. We first model the sun tracking error, which could be measured using BCS (Beam Characterization System), by multilayered neural network. Then the extended Kalman filter was employed to train the neural network. Finally the model is used to compensate the sun tracking errors. Simulated result shows that the method proposed in this paper improve the heliostat sun tracking performance dramatically. It also shows that the training of neural network by the extended Kalman filter provides faster convergence property, more accurate estimation and higher measurement noise rejection ability compared with the other training methods like gradient descent method.

• The Journal of the Acoustical Society of Korea
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• v.20 no.6
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• pp.17-25
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• 2001

Traditional adaptive noise cancelling methods rely their performance on various interfering parameters, such as convergence speed, tracking ability, numerical stability, relative frequency characteristics between target and reverberation signals, and activity of the target. In this paper, an adaptive noise cancelling method is suggested, which Provides a successful tradeoff mon these factors. It is designed to work on the transform domain, adopts the Gram-Schmidt orthogonalization process, and is implemented by the escalator algorithm. The transform domain approach supports a tradeoff between the convergence speed and numerical cost. The proposed method is verified by applying a real-data collected in the shallow waters off the east coasts of korea. It is shown that it has a good reverberation-rejection capability even for the target signal with adjacent frequency components to those of the reverberation, and its performance is invariant for the activity of the target.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.8
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• pp.241-248
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• 2022

In this paper, the PID controller and Kalman filter are applied to improve the automobile cruise control in the environment with disturbance and noise, and the performance is verified through diverse simulation. First, a mathematical model for a automobile cruise control system is introduced. Second, the performance degradation due to disturbance in the basic open-loop control based cruise control system is shown and then PID controller-based feedback control system to resolve this problem is verified. Third, to improve the performance degradation due to sensor noise that may occur during the feedback process, a Kalman filter is applied and verified. Ultimately, it is verified that the designed cruise control system with PID controller and Kalman filter not only satisfies all performance conditions but also has the ability for disturbance rejection and noise reduction.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.2 s.3
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• pp.1-12
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• 2003

DAB(Digital audio broadcasting) is a next generation radio broadcasting system which provides CD quality audio, various data services and superior reception ability when moving. Also, it can show traffic informations and news literally or graphically. In this paper, we design and fabricate the DAB tuner for ITS service that follows Eureka-147 and ETSI 300 401 specifications. This small-sized tuner can be adopted to mny electronic equipments such as a Hi-Fi audio, DVD player, car audio system etc.. The overall performance of the tuner depends on a phase noise of VCO and the sensitivity of the receiving system is influenced by LNA, image rejection filter and channel selection filter. All our measurement results satisfy the specification for a DAB system with the return loss of 9dB, the noise figure of 6dB for both Band 111 and L-band and the sensitivity of -97dBm.

• The Journal of the Acoustical Society of Korea
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• v.21 no.1
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• pp.62-68
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• 2002

It is well known that the MDVR beamforming outperforms the conventional delay-sum beamformer in the sense of noise rejection and bearing resolution. However, the MDVR method requires long observation time to achieve high frequency resolution. The STMV method uses the steered covariance matrix of sensor data, so it has an ability to form an adaptive weight vector from a single time-series snapshot. But it uses the same weight vector across all frequencies. In this paper, we propose an SSMV method. The basic idea of the SSMV method is to decompose a full frequency band into several subbands to acquire a weight vector for each subband, individually. Also the wrap may be divided into several subarrays in order to reduce a computational load and the bandwidth of each subband. Simulations using real sea trial data show that the proposed SSMV method has good performance with short observation time.