• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.77-82
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• 2018

This paper is concerned with the performance analysis of a modified stop-and-go generalized multi-modulus algorithm (MSAG-GMMA) adaptive blind equalization algorithm with variable step size. The proposed algorithm multiplies the fixed step size by the error signal of the decision-oriented algorithm in the equalization coefficient update equation, and changes the step size according to the error size. Also, the MSAG-GMMA having a fixed step size is operated so as to maintain a fast convergence speed from a certain threshold to a steady state by determining the error signal size of the decision-directed algorithm, and when the MSAG-GMMA to work To evaluate the performance of the proposed algorithm, we use the ensemble ISI, ensemble-averaged MSE, and equalized constellation obtained from the output of the equalizer as the performance index. Simulation results show that the proposed algorithm has faster convergence speeds than MMA, GMMA, and MSAG-GMMA and has a small residual error in steady state.

• Journal of Power Electronics
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• v.15 no.6
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• pp.1619-1627
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• 2015

This paper presents a power system harmonic elimination using the mixed adaptive linear neural network and variable step-size leaky least mean square (ADALINE-VSSLLMS) control algorithm based active power filter (APF). The weight vector of ADALINE along with the variable step-size parameter and leakage coefficient of the VSSLLMS algorithm are automatically adjusted to eliminate harmonics from the distorted load current. For all iteration, the VSSLLMS algorithm selects a new rate of convergence for searching and runs the computations. The adopted shunt-hybrid APF (SHAPF) consists of an APF and a series of 7^th tuned passive filter connected to each phase. The performance of the proposed ADALINE-VSSLLMS control algorithm employed for SHAPF is analyzed through a simulation in a MATLAB/Simulink environment. Experimental results of a real-time prototype validate the efficacy of the proposed control algorithm.

• The Transactions of the Korean Institute of Power Electronics
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• v.24 no.1
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• pp.1-8
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• 2019

In this study, a maximum power point tracking (MPPT) algorithm based on the perturb and observe (P&O) method with variable step size is proposed to improve the dynamic response characteristic of MPPT, using the existing P&O method. The proposed algorithm, which we verified by simulation and experiment, can track the maximum power point (MPP) through duty control and consisted of three operation modes, namely, constant voltage mode, fast mode, and variable step mode. When the insolation is constant, the voltage variation of the operating point at the MPP is reduced through the step size reduction of the duty in the variable step mode. Consequently, the vibration of the operating point is reduced, and the power generation efficiency is increased. When the insolation changes, the duty and the photovoltaic (PV) voltage are kept constant through the constant voltage mode. The operating point then rapidly tracks the new MPP through the fast-mode operation at the end of the insolation change. When the MPP is reached, the operation is changed to the variable step mode to reduce the duty step size and track the MPP. The validity of the proposed algorithm is verified by simulation and experiment of a PV system composed of a PV panel and a boost converter.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.443-448
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• 2022

This paper presents a subband affine projection algorithm with variable step size to improve convergence performance in adaptive filtering applications with long adaptive filters and highly correlated input signals. The proposed algorithm can obtain fast convergence speed and small steady-state error by using different step sizes for each adaptive sub-filter in the subband structure to which polyphase decomposition and noble identity are applied. The step size derived to minimize the mean square error of the adaptive filter at each update time shows better convergence performance than the existing algorithm using a variable step size. In order to confirm the convergence performance of the proposed algorithm, which is superior to the existing algorithm, computer simulations are performed for mean square deviation(MSD) for AR(1) and AR(2) colored input signals considering the system identification model.

• The Journal of the Acoustical Society of Korea
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• v.26 no.2
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• pp.69-74
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• 2007

In signal processing applications with highly correlated input signals, subband affine projection algorithm and step size controlling is a good solution for improving the slow convergence rate and large computational complexity of LMS-type algorithms. This paper proposes a subband affine projection algorithm using a variable step size. The proposed method achieves fast convergence rate and small steady-state error with a small computational complexity by combining the SAP and step size controlling in a subband structure. Experimental results on highly correlated input signal show that the proposed method is superior to the conventional methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.107-112
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• 2016

This paper proposes the improving the equalization performance using the variable step size in the S-MMA (Sliced-Multi Modulus Algorithm) equalization algorithm in order to minimize the effect of intersymbol interference which occurs at the nonlinear transfer function of communication channel. The S-MMA were showned for the improving the steady state equalization performance and misadjustment compared to the MMA present algorithm, this two algorithm has a limitation of performance improvement due to the adapting the fixed step size according to the error signal amplitude. In order to solving the abovemensioned problem, the proposed algorithm was adopting the variable step size proportional to the error signal amplitude and the computer simulation was performed for showing the performance improving. As a result of simulation, the proposed VSS S-MMA algorithm has more superior equalization performance compared to the present S-MMA.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3
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• pp.245-250
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• 2009

In communications and signal processing area, a number of least mean square adaptive algorithms have been used because of simplicity and robustness. However the LMS algorithm is known to have slow and non-uniform convergence. Various variable step size LMS adaptive algorithms have been introduced and researched to speed up the convergence rate. A variable step size LMS algorithm using the error difference for updating the step size is proposed. Compared with other algorithms, simulation results show that the proposed LMS algorithm has a fast convergence. The theoretical performance of the proposed algorithm is also analyzed for the steady state.

• Journal of Korea Multimedia Society
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• v.8 no.6
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• pp.753-760
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• 2005

This paper introduces a variable step-size adaptive algorithm for blind source separation. From the frequency characteristics of mixed input signals, we need to adjust the convergence speed regularly in each frequency bin. This algorithm varies a step-size according to the magnitude of input at each frequency bin. This guarantee of the regular convergence in each frequency bin would become more efficient in separation performances than conventional fixed step-size FDICA. Computer simulation results show the improvement of about 5 dB in signal to interference ratio (SIR) and the better separation quality.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3E
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• pp.93-98
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• 2009

In this paper, we propose a new VSS-NLMS algorithm through a simple modification of the conventional NLMS algorithm, which leads to a low complexity algorithm with enhanced performance. The step size of the proposed algorithm becomes smaller as the error signal is getting orthogonal to the input vector. We also show that the proposed algorithm is an approximated normalized version of the KZ-algorithm and requires less computation than the KZ-algorithm. We carried out a performance comparison of the proposed algorithm with the conventional NLMS and other VSS algorithms using an adaptive channel equalization model. It is shown that the proposed algorithm presents good convergence characteristics under both stationary and non-stationary environments despites its low complexity.

• Journal of Power Electronics
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• v.11 no.2
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• pp.218-227
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• 2011

The subject of variable step size maximum power point tracking (MPPT) algorithms has been addressed in the literature. However, most of the addressed algorithms tune the variable step size according to two variables: the photovoltaic (PV) array voltage ($V_{PV}$) and the PV array current ($I_{PV}$). Therefore, both the PV array current and voltage have to be measured. Recently, maximum power point trackers that arc based on a single variable ($I_{PV}$ or $V_{PV}$) have received a great deal of attention due to their simplicity and ease of implementation, when compared to other tracking techniques. In this paper, two methods have been proposed to design a variable step size MPPT algorithm using only a single current sensor for stand-alone battery storage PV systems. These methods utilize only the relationship between the PV array measured current and the converter duty cycle (D) to automatically adapt the step change in the duty cycle to reach the maximum power point (MPP) of the PV array. Detailed analyses and flowcharts of the proposed methods are included. Moreover, a comparison has been made between the proposed methods to investigate their performance in the transient and steady states. Finally, experimental results with field programmable gate arrays (FPGAs) are presented to verify the performance of the proposed methods.