• The Journal of the Acoustical Society of Korea
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• v.28 no.8
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• pp.815-821
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• 2009

Information processing in variable and noisy environments is usually accomplished by means of adaptive filters. Among various adaptive algorithms, Least Mean Square (LMS) has become the most popular for its robustness, good tracking capabilities and simplicity, both in terms of computational load and easiness of implementation. In practical application of the LMS algorithm, the most important key parameter is the Step Size. As is well known, if the Step Size is large, the convergence rate of the algorithm will be rapid, but the steady state mean square error (MSE) will increase. On the other hand, if the Step Size is small, the steady state MSE will be small, but the convergence rate will be slow. Many researches have been proposed to alleviate this drawback by using a variable Step Size. In this paper, a new variable Step Size LMS(VSSLMS) called Categorized VSSLMS (CVSSLMS) is proposed. CVSSLMS updates the Step Size by categorizing the current status of the gradient, hence significantly improves the convergence rate. The performance of the proposed algorithm was verified from the view point of convergence rate, Excessive Mean Square Error(EMSE), and complexity through experiments.

• 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 Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.3C
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• pp.157-162
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• 2011

For blind equalization of communication channels, concurrent equalization is useful to improve convergence characteristics. However, the concurrent equalization will result in limited performance enhancement by continuing concurrent adaptation with two algorithms after the equalizer converges to steady-state. In this paper, to improve the convergence characteristics and steady-state performance of the concurrent equalization, proposed is a new concurrent equalization technique with variable step-size parameter and weight-based tap coefficients update. The proposed concurrent vsCMA+DD equalization calculates weight factors using error signals of the variable step-size CMA (vsCMA) and DD (decision-directed) algorithm, and then updates the two equalizers based on the weights respectively. The proposed method, first, improves the error performance of the CMA by the vsCMA, and enhances the steady-state performance as well as the convergence speed further by the weight-based tap coefficients update. The performance improvement by the proposed scheme is verified through simulations.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.129-135
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• 2011

The alternate adaptation algorithm (AAA) is proposed to improve the convergence characteristics and steady-state performance of the constant modulus algorithm (CMA). The alternate adaptation algorithm is a new equalization method which adapts an equalizer alternately by the algorithm with excellent blind convergence characteristics or the algorithm with better steady-state error performance. In this paper, it is introduced that the alternate adaptation equalization of the vsCMA (variable step-size CMA) and the decision-directed (DD) algorithm. We, first, designed the vsCMA with variable step-size to improve the steady-state error performance of the CMA, and combined it with the DD by alternate adaptation. As a result, it was mitigated that the sensitivity of performance fluctuation due to switching timing in CMA-DD switching method, and it was improved that the convergence speed and steady-state error performance of the CMA. Through computer simulations, under multipath channel condition, the usefulness of the proposed method was confirmed for 16-QAM.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2366-2377
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• 1997

An Adaptive Usage Parameter Control(UPC) mechanism using a Variable Token Pool(VTP) which is kind of preventive traffic control in the Asynchronous Transfer Mode(ATM) networks is described. The VTP mechanism can monitor violations of the average bit rate and burst duration as well as peak bit rate for the ON-OFF type traffic. The VTP can vary the token pool size by monitoring burst duration and silence duration for a long term. It also improves the sensitivity against the violation of burst duration and average bit rate and enables to response for the violating traffic situation quickly. The variable token pool size is varied in step size by every burst duration and silence duration. Two important parameters for controlling token pool size are Down_size and Up_size. We compare the performance of LB and JW mechanism with the proposed VTP mechanism by computer simulations. We have known that the proposed method is more effective than the previous mechanisms. It is shown that the cell loss rate of the VTP quite depends on the value of Down_size and Up_size. The two parameters should be decided as a propr value according to traffic situations.

• Proceedings of the Korea Contents Association Conference
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• 2005.05a
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• pp.369-373
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• 2005

This paper proposes a variable step size parameter method in frequency domain ICA (FDICA). The FDICA and the temporal analysis (TA) algorithm are experimented for blind source separation (BSS). This paper will compare the separation qualities of these two algorithms in various reverberation environments. Furthermore, it is shown that the proposed technique has the better separation performance than those of two methods especially in recorded data.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.4
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• pp.42-49
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• 1997

A conventional adaptive noise canceller (ANC) using LMS algorithm suffers from the misadjustment of adaptive filter weights due to the gradient-estimate noise by input speech signal at steady state. In this paper, an ANC is proposed which uses the combination of VSLMS (variable step size LMS) and SA (sign algorithm) to improve steady state performance and convergence rate. SA algorithm is applied in speech region to prevent the weights from perturbing by output speech of ANC and VSLMS algorithm is applied to improve convergence rate and channel tracking ability in silence region and adaptive transient region. In compute rsimulation, the performance of the proposed VSLMS-SA combination algorithm is much better than LMS algorithm and the algorithm, recently proposed by greenberg, with adaptation step-size parameter determine dby sum method in convergence rate, channel tracking and steady state performance.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.689-692
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• 2003

In this paper, we propose an adaptive beamforming algorithm for array antenna. The proposed beamforming algorithm, based on Block LMS (Block - Least Mean Squares) algorithm, has a variable step size from coefficient update. This method shows some advantages that the convergence speed is fast and the calculation time can reduced using a block LMS algorithm from frequency domain. As the adaptive parameter approaches a stationary state, it could reduce the number of filter coefficient update with the help of various step size. In this paper we compared the efficiency of the proposed algorithm with a standard LMS algorithm which is a representative method of adaptive beamforming.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.6
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• pp.45-53
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• 1996

In this paper, the convergence behavior of timing phase when an adaptive partial response equalizer and decision-directed type of a PLL work together in a digital recording channel is described. The phenomena of getting biased in timing phase when the convergence parameter of an adaptive partial response equalizer and timing recovery constant of a PLL are not selected properly is introduced. The phenomena, occurring due to perturbation of timing phase, are analyzed, by computer simulation and the region of ocnvergence for timing phase is discussed. Also, a method to overcome the phenomena using a variable step-size parameter is described.

• ETRI Journal
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• v.32 no.5
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• pp.795-800
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• 2010

Embedding a large vocabulary speech recognition system in mobile devices requires a reduced acoustic model obtained by eliminating redundant model parameters. In conventional optimization methods based on the minimum description length (MDL) criterion, a binary Gaussian tree is built at each state of a hidden Markov model by iteratively finding and merging similar mixture components. An optimal subset of the tree nodes is then selected to generate a downsized acoustic model. To obtain a better binary Gaussian tree by improving the process of finding the most similar Gaussian components, this paper proposes a new distance measure that exploits the difference in likelihood values for cases before and after two components are combined. The mixture weight of Gaussian components is also introduced in the component merging step. Experimental results show that the proposed method outperforms MDL-based optimization using either a Kullback-Leibler (KL) divergence or weighted KL divergence measure. The proposed method could also reduce the acoustic model size by 50% with less than a 1.5% increase in error rate compared to a baseline system.