• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2087-2089
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• 2003

The presence of narrowband interference (NBI) in Direct-sequence code division multiple access (DS/CDMA) systems is an inevitable problem when the interference is strong enough. The improvement in the system performance employs by adaptive narrowband interference suppression techniques. Basically there have been two types of method for narrowband interference suppression estimator/subtracter approaches and transform domain approaches. In this paper the focus is on the type of estimator/subtracter approaches. However, the binary direct sequence (DS) signal, that acts as noise in the prediction process is highly non-Gaussian. The case of a Gaussian interferer with known in an autoregressive (AR) signal or a digital signal and also in a sinusoidal signal (Tone) that included in is paper. The proposed NBI suppression is presence in an adaptive IIR notch filter for lattice structure and more powerful by using a variable step-size algorithm. The simulation results show that the proposed algorithm can significantly increase the convergence rate and improved system performance when compare with adaptive least mean square algorithm (LMS).

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.87.2-87
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• 2002

$\textbullet$ Introduction of an adaptive echoes canceller in telephone network and the propose $\textbullet$ The echoes canceller structure $\textbullet$The Lattice/Transversal Joint structure $\textbullet$ The propose robust variable step-size algorithm for lattice form structure $\textbullet$ Performance evaluation $\textbullet$ Simulation results $\textbullet$ Conclusion

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.285-286
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• 2008

In this paper, we propose adaptive search channel estimate algorithm. The proposed algorithm is modified LMS algorithm which has a variable step size and parallel convolution. In simulation result, a error estimate accuracy of the proposed algorithm is about -20 dB and general LMS algorithm is about 10 dB. The proposed algorithm is better error estimate accuracy than general LMS algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.823-828
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• 1992

A novel steepest descent adaptive filter algorithm, which uses the instantaneous stochastic gradient for the steepest descent direction, is derived from a newly devised performance index function. The performance function for the new algorithm is improved from that for the LMS in consideration that the stochastic steepest descent method is utilized to minimize the performance index iterativly. Through mathematical analysis and computer simulations, it is verified that there are substantial improvements in convergence and misadjustments even though the computational simplicity and the robustness of the LMS algorithm are hardly sacrificed. On the other hand, the new algorithm can be interpreted as a variable step size adaptive filter, and in this respect a heuristic method is proposed in order to reduce the noise caused by the step size fluctuation.

• Proceedings of the KIPE Conference
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• 2010.07a
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• pp.565-567
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• 2010

This paper proposes a new Maximum Power Point Tracking (MPPT) control algorithm for PV-Cell (Photo voltaic) based on Incremental Conductance MPPT algorithm. The ICN (Incremental Conductance method) algorithm is widely used due to the high tracking accuracy and adaptability to the rapidly changing isolation condition. In this paper, a modified ICN MPPT algorithm is proposed. This method adjusts automatically the step-size of reference to track the PV-Cell maximum power point, thus it improves the maximum power point tracking speed and accuracy.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.9
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• pp.1420-1427
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• 1989

A new block matching algorithm that improved the existing block matching algorithm in terms of image quality is proposed in this paper. The subblock of image including the vertical edge of object is subdivided into new two subblocks, and the moving vector found. The result of computer simulation shows on real image that the image quality by the algorithm becomes higher than that of the three step search algorithm by 1.1dB.

• The Journal of the Acoustical Society of Korea
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• v.28 no.7
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• pp.640-645
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• 2009

CMA (Constant Modulus Algorithm) is one of the famous algorithms in blind channel equalization. Generally, CMA converges slowly and the speed of convergence is dependent on a step-size in the CMA procedure. Many researches have tried to speed up the convergence speed by applying a variable step-size to CMA. In this paper, we propose a new CMA algorithm with improved convergence performance. The improvement comes from an orthogonal projection of an average error gradient. We show the improvement in simulation results.

• The Journal of the Acoustical Society of Korea
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• v.34 no.5
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• pp.394-402
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• 2015

CMA (Constant Modulus Algorithm) is one of the well-known algorithms in blind acoustic channel equalization. Generally, CMA converges slowly and the speed of convergence is dependent on a step-size in the CMA procedure. Many researches have tried to speed up the convergence speed by applying a variable step-size to CMA, e.g. the orthogonal projection CMA and algebraic optimal step-size CMA. In this paper, we summarize these two algorithms, and we propose a new CMA with improved convergence performance. The improvement comes from the switching between the orthogonal projection CMA and algebraic optimal step-size CMA. In simulation results, we show the performance improvement in the time invariant channels as well as in time varying channel.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.4
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• pp.17-21
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• 2002

Least mean square(LMS) algorithm one of the most popular algorithm in adaptive signal processing because of the simplicity and the small computation. But the convergence speed of time domain adaptive algorithm is slow when the spread width of eigen values is wide. Moreover we have to choose the step size well for convergency. in this paper, ie use adaptive algorithm of wavelet transform. And we propose a new wavelet based adaptive algorithm of wavelet transform. And we propose a high speed wavelet based adaptive algorithm with variable step size, which is linear to absolute value of error signal. We applied this algorithm to adaptive noise canceler. Simulation results are presented to compare the performance of the proposed algorithm with the usual algorithms.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.95-101
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• 2009

Among the adaptive noise cancellers (ANC), the least mean square (LMS) algorithm has probably become the most popular algorithm because of its robustness, good tracking properties, and simplicity of implementation. However, it has non-uniform convergence and a trade-off between the rate of convergence and excess mean square error (EMSE). To overcome these shortcomings, a number of variable step size least mean square (VSSLMS) algorithms have been researched for years. These LMS algorithms use a complex variable step method approach for rapid convergence but need high computational complexity. A variable step approach can impair the simplicity and robustness of the LMS algorithm. The proposed instantaneous gain control (IGC) algorithm uses the instantaneous gain value of the original signal and the noise signal. As a result, the IGC algorithm can reduce computational complexity and maintain better performance.