• Journal of Power Electronics
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• v.17 no.2
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• pp.533-541
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• 2017

This paper presents a novel Parameter-Independent Fictive-Axis (PIFA) approach for the Voltage-Oriented Control (VOC) algorithm used in grid-tied single-phase inverters. VOC is based on the transformation of the single-phase grid current into the synchronous reference frame. As a result, an orthogonal current signal is needed. Traditionally, this signal has been obtained from fixed time delays, digital filters or a Hilbert transformation. Nevertheless, these solutions present stability and transient drawbacks. Recently, the Fictive Axis Emulation (FAE) VOC has emerged as an alternative for the generation of the quadrature current signal. FAE requires detailed information of the grid current filter along with its transfer function for signal creation. When the transfer function is not accurate, the direct and quadrature current components present steady-state oscillations as the fictive two-phase system becomes unbalanced. Moreover, the digital implementation of the transfer function imposes an additional computing burden on the VOC. The PIFA VOC presented in this paper, takes advantage of the reference current to create the required orthogonal current, which effectively eliminates the need for the filter transfer function. Moreover, the fictive signal amplitude and phase do not change with a frequency drift, which results in an increased reliability. This yields a fast, linear and stable system that can be installed without fine tuning. To demonstrate the good performance of the PIFA VOC, simulation and experimental results are presented.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.85-91
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• 2014

This paper relates with the VSDA (Variable stepsize Square contour Decision directed Algorithm) adaptive equalization algorithm that is used for the minimization of the intersymbol interference due to the distortion which occurs in the time dispersive channel for the transmission of 16-QAM signal.. In the conventional SCA, it is possible to compensates the amplitude and phase in the received signal that are mixed with the intersymbol interference by the constellatin dependent constant by using the 2nd order statistics of the transmitted signal. But in the VSDA, it is possible to the increasing the equalization performance by adding the concept of distance adjusted approach for constellation matching and the cost function of decision directed. We compare the performance of VSDA and SCA algorithm by the computer simulation. For this, the equalizer output signal constellation, residual isi, maximum distortion and MSE were used in the performace index. As a result of computer simulation, the VSDA algorithm has better than the SCA in convergence speed, but it gives nearly same equalization performance in other index.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.67-73
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• 2013

This paper relates with the performance of VSCA adaptive equalization algorithm that is used for the minimization of the intersymbol interference due to the distortion which occurs in the time dispersive channel for the transmission of 16-QAM signal. In the conventional SCA, it is possible to compensates the amplitude and phase in the received signal that are mixed with the intersymbol interference by the constellatin dependent constant by using the 2nd order statistics of the transmitted signal. But in the VSCA, it is possible to the increase the equalization performance by adding the concept of distance adjusted approach for constellation matching. We compare the performance of VSCA and SCA algorithm by computer simulation. For this, the equalizer output signal constellation, residual isi, maximum distortion and MSE were used for perfomance comparison. It was confirmed that, the VSCA algorithm has better than the SCA in every performance index by computer simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.986-992
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• 2021

To stabilize closed-loop wireless control systems, the state-of-the-art approach receives the individual sensor measurements at the controller and then sends the computed control signal to the actuators. We propose an over-the-air controller scheme where all sensors attached to the plant transmit scaled sensing signals simultaneously to the actuator, and the actuator then computes the feedback control signal by scaling the received signal. The over-the-air controller essentially adopts the over-the-air computation concept to compute the control signal for closed-loop wireless control systems. In contrast to the state-of-the-art sensor-to-controller and controller-to-actuator communication approach, the over-the-air controller exploits the superposition properties of multiple-access wireless channels to complete the communication and computation of a large number of sensing signals in a single communication resource unit. Therefore, the proposed scheme can obtain significant benefits in terms of low actuation delay and low resource utilization with a simple network architecture that does not require a dedicated controller.

• Journal of Power Electronics
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• v.17 no.2
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• pp.501-513
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• 2017

The fundamental small-signal modeling of lithium-ion (Li-ion) batteries and a parameter evaluation approach are investigated in this study to describe the dynamic behaviors of small signals accurately. The main contributions of the study are as follows. 1) The operational principle of the small signals of Li-ion batteries is revealed to prove that the sinusoidal voltage response of a Li-ion battery is a result of a sinusoidal current stimulation of an AC small signals. 2) Three small-signal measurement conditions, namely stability, causality, and linearity, are proved mathematically proven to ensure the validity of the frequency response of the experimental data. 3) Based on the internal structure and electrochemical operational mechanism of the battery, an AC small-signal model is established to depict its dynamic behaviors. 4) A classical least-squares curve fitting for experimental data, referred as Levy's method, are introduced and developed to identify small-signal model parameters. Experimental and simulation results show that the measured frequency response data fit well within reading accuracy of the simulated results; moreover, the small-signal parameters identified by Levy's method are remarkably close to the measured parameters. Although the fundamental and parameter evaluation approaches are discussed for Li-ion batteries, they are expected to be applicable for other batteries.

• The Journal of the Acoustical Society of Korea
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• v.32 no.2
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• pp.131-137
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• 2013

In this paper we propose an improved voice activity detection (VAD) algorithm using statistical models in the signal subspace domain. A uncorrelated signal subspace is generated using embedded prewhitening technique and the statistical characteristics of the noisy speech and noise are investigated in this domain. According to the characteristics of the signals in the signal subspace, a new statistical VAD method using GGD (Generalized Gaussian Distribution) is proposed. Experimental results show that the proposed GGD-based approach outperforms the Gaussian-based signal subspace method at 0-15 dB SNR simulation conditions.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.1060-1071
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• 2014

Signals of the Electroencephalogram (EEG) can reflect the electrical background activity of the brain generated by the cerebral cortex nerve cells. This has been the mostly utilized signal, which helps in effective analysis of brain functions by supervised learning methods. In this paper, an approach for improving the accuracy of EEG signal classification is presented to detect epileptic seizures. Moreover, Independent Component Analysis (ICA) is incorporated as a preprocessing step and Short Time Fourier Transform (STFT) is used for denoising the signal adequately. Feature extraction of EEG signals is accomplished on the basis of three parameters namely, Standard Deviation, Correlation Dimension and Lyapunov Exponents. The Artificial Neural Network (ANN) is trained by incorporating Levenberg-Marquardt(LM) training algorithm into the backpropagation algorithm that results in high classification accuracy. Experimental results reveal that the methodology will improve the clinical service of the EEG recording and also provide better decision making in epileptic seizure detection than the existing techniques. The proposed EEG signal classification using feed forward Backpropagation Neural Network performs better than to the EEG signal classification using Adaptive Neuro Fuzzy Inference System (ANFIS) classifier in terms of accuracy, sensitivity, and specificity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.6
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• pp.773-778
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• 1993

A new approach is proposed for the DCT which is widely utilized in the image processing, The approach replaces mutiplications with shift and additions, In the image restored by the proposed DCT and IDCT, no visible degration is observed and PSNR(Peak to Peak Signal to Noise Ratio) is greater than 35 dB for all cases, proving the usefulness of the proposal.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.42-48
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• 1994

In this paper, a low power and high speed flash Analog-to-Digital Converter using current-mode concept is proposed. Current-mode approach offers a number of advantages over conventional voltage-mode approach, such as lower power consumption small chip area improved accuracy etc. Rescently this concept was applied to algorithmic A/D Converter. But, its conversion speed is limited to medium speed. Consequently this converter is not applicable to the high speed signal processing system. This ADC is fabricated in 1.2um double metal CMOS standard process. This ADC's conversion time is measured to be 7MHz, and power consumption is 2.0mW, and differential nonlinearity is less than 1.14LSB and total harmonic distortion is -50dB. The active area of analog chip is about 350 x 550u$m^2$. The proposed ADC seems suitable for a single chip design of digital signal processing system required high conversion speed, high resolution small chip area and low power consumption.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.1
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• pp.222-228
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• 2003

A reliable tool wear monitoring technique is the one of important aspects for achieving an integrated and self-adjusting manufacturing system. In this paper, a tool wear estimation approach for turning is proposed. This approach uses the model of cutting force, spindle displacement and their relation. A series of experiments were conducted by designing experimental techniques to determine the relationship between flank wear and cutting force coefficient as well as cutting parameters such as cutting speed, depth of cut and feed. The proposed model performance has shown that the spindle displacement model predicts tool wear with high accuracy and spindle displacement signal is possible to replace cutting force signal.