• The Journal of Korean Institute of Communications and Information Sciences
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• 제29권1A호
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• pp.9-17
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• 2004

Adapt ive and fixed step size PC (power control) schemes for accommodating voice, video, and data are evaluated according to the different PC command rates and their effects on integrated Voice/Video/Data are investigated. The required minimum power levels are derived as PC thresholds and the effects of PC errors on channel quality and radio 1 ink capacity are investigated. The services with high bit rates and low bit error rates can cause a significant effect on the radio link qualifies of the other types of traffic. The results show that the adapt ive step size PC scheme for voice/video/data services can achieve more capacity and cause less interference to the radio channels because less minimum PIL(Power Increment Level) is required for the specified radio link outage probability.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.941-946
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• 2005

In this paper an active random noise control using adaptive learning rate neural networks is presented. The adaptive learning rate strategy increases the learning rate by a small constant if the current partial derivative of the objective function with respect to the weight and the exponential average of the previous derivatives have the same sign, otherwise the learning rate is decreased by a proportion of its value. The use of an adaptive learning rate attempts to keep the learning step size as large as possible without leading to oscillation. It is expected that a cost function minimize rapidly and training time is decreased. Numerical simulations and experiments of active random noise control with the transfer function of the error path will be performed, to validate the convergence properties of the adaptive learning rate Neural Networks. Control results show that adaptive learning rate Neural Networks control structure can outperform linear controllers and conventional neural network controller for the active random noise control.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제22권10호
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• pp.2339-2347
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• 1997

The performance of the adaptive noise canceller using LMS algorithm is degraded by the gradient noise due to target speech signals. An adaptive noise canceller with speech detector was proposed to reduce this performande degradation. The speech detector utilized the adaptive prediction-error filter adapted by the NLMS algorithm. This paper discusses to enhance the performance of the adaptive noise canceller forthecorlored noise. The affine projection algorithm, which is known as faster than NLMS algorithm for correlated signals, is used to adapt the adaptive filter and the adaptive prediction error filter. When the voice signals are detected by the speech detector, coefficients of adaptive filter are adapted by the sign-error afine projection algorithm which is modified to reduce the miaslignment of adaptive filter coefficients. Otherwirse, they are adapted by affine projection algorithm. To obtain better performance, the proper step size of sign-error affine projection algorithm is discussed. As resutls of computer simulation, it is shown that the performance of the proposed ANC is better than that of conventional one.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1854-1857
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• 1991

A numerically efficient modification of a variable step size LMS (Least Mean Squares) algorithm is proposed. This proposed algorithm is very simple in calculation and has a variable step size adjusted by the filter output error. Its additional computational burden with respect to the conventional LMS algorithm is only two multiplications, two substraction, an addition and some bit operations. In a simulation example, it is shown that the proposed algorithm has not only the faster convergence rate but also less misadjustments in the environment of highly nonstationary and correlated data.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제8권3호
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• pp.113-119
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• 1983

In this paper, a method of the step size adaption is studied on the delta modulation coding of speech signals. Exponential adaption processes are reserched by a new circuit model. It is presented a shorten error recovery in decoder step size. Practical considerations favor one algorithm, and its digital implementation has been adapted for the illustration of above method, using the rate multipliers and the validity is verified by laboratory experiment.

• Nonlinear Functional Analysis and Applications
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• 제27권1호
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• pp.121-140
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• 2022

In this paper, we study the strong convergence of new methods for solving classical variational inequalities problems involving semistrictly quasimonotone and Lipschitz-continuous operators in a real Hilbert space. Three proposed methods are based on Tseng's extragradient method and use a simple self-adaptive step size rule that is independent of the Lipschitz constant. The step size rule is built around two techniques: the monotone and the non-monotone step size rule. We establish strong convergence theorems for the proposed methods that do not require any additional projections or knowledge of an involved operator's Lipschitz constant. Finally, we present some numerical experiments that demonstrate the efficiency and advantages of the proposed methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제18권3호
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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 the Korea Institute of Information and Communication Engineering
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• 제9권1호
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• pp.22-33
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• 2005

In this paper, an efficient signal interference control technique to improve the high convergence speed of LMS algorithms is introduced in the adaptive transversal filter of DS/SS. The convergence characteristics of the proposed algorithm, whose coefficients are multiply adapted in a symbol time period by recycling the received data, is analyzed to prove theoretically the improvement of high convergence speed. According as the step-size parameter ${\mu}$ is increased, the rate of convergence of the algorithm is controlled. Also, an increase in the stop-size parameter ${\mu}$ has the effect of reducing the variation in the experimentally computed learning curve. Increasing the eigenvalue spread has the effect of controlling which is downed the rate of convergence of the adaptive equalizer. Increasing the steady-state value of the average squared error, proposed algorithm also demonstrate the superiority of signal interference control to the filter algorithm increasing convergence speed by (B+1) times due to the data-recycling LMS technique.

• ETRI Journal
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• 제45권6호
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• pp.996-1006
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• 2023

Renewable energy is promoted massively to overcome problems that fossil fuel power plants generate. One popular renewable energy type that offers easy installation is a photovoltaic (PV) system. However, the energy harvested through a PV system is not optimal because influenced by exposure to solar irradiance in the PV module, which is constantly changing caused by weather. The maximum power point tracking (MPPT) technique was developed to maximize the energy potential harvested from the PV system. This paper presents the MPPT technique, which is operated on a new high-gain voltage DC/DC converter that has never been tested before for the MPPT technique in PV systems. Fuzzy logic (FL) was used to operate the MPPT technique on the converter. Conventional and adaptive perturb and observe (P&O) techniques based on variables step size were also used to operate the MPPT. The performance generated by the FL algorithm outperformed conventional and variable step-size P&O. It is evident that the oscillation caused by the FL algorithm is more petite than variables step-size and conventional P&O. Furthermore, FL's tracking speed algorithm for tracking MPP is twice as fast as conventional P&O.

• 전자공학회논문지 IE
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• 제43권4호
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• pp.37-42
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• 2006

This paper proposes a adaptive video watermarking algorithm according to bitrate and motion vector size in MPEG2 system. The watermark strength in the I-frames is adapted for quantization step size and the strength in the P-B-frames is adapted for quantization step size and motion vector of macroblock to make the watermark more robust against the accompanying degradation due to aggressively compression. A realtime watermark extraction is done directly in the DCT domain during MPEG decoding without full decoding of MPEG video. The experimental simulations show that the video quality results almost invisible difference between the watermarked frames and the original frames and the watermark is resistant to frame dropping, MPEG compression, GoP conversion and low pass filter attacks.