• Journal of the Korean Institute of Telematics and Electronics
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• v.21 no.2
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• pp.29-35
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• 1984

LMS algorithm is used widely in adaptive filtering because of its simplicity. In this paper it is shown that the one dimensional LMS adaptive filter can be extended in the two dimensional adaptive filter and the methods for improving the convergence rate and the several problems inherent in the two dimensional adaptive filter are discussed.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.163-166
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• 2010

본 논문에서는 현재 상용화 되어있는 WCDMA용 ICS (Interference Cancellation System) 중계기의 성능 개선을 위한 개선된 LMS 알고리즘을 연구하였다. ICS 중계기의 수신으로 입력되는 신호는 수신 신호와 궤환되어 입력되는 신호로 구성된다. 이렇게 입력되는 궤환 신호를 LMS와 같은 적응형 채널 추정 알고리즘을 통해 제거하는 기술이 ICS 중계기의 핵심 요소이다. 중계기의 저비용 및 단순화를 위해서는 기존에 사용되어온 적응형 채널 추정 알고리즘의 단순화가 필요하다. 실험을 통해 기존 NLMS 알고리즘 및 계산 복잡도 감소를 위해 수정된 LMS 알고리즘을 MSE (Mean Square Error) 기준에서 성능 비교를 하였다.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1967-1968
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• 2008

본 논문에서는 안정성이 강화된 다중채널 적응 필터를 사용한 능동소음 제어 시스템을 제안한다. 초기에는 IIR필터의 극점을 원점방향으로 강제로 이동시켜 안정성을 확보하고, 망각인수를 도입하여 정상상태에 도달하면 최적 수렴치로 유지하게 함으로서 제어 정상상태 성능에는 영향을 미치지 않고 안정도가 강화 된 적응 IIR 필터 알고리즘을 제안한다. LMS 알고리즘의 수렴 성능을 개선하기 위한 방법으로 정규화기법을 사용하면 수렴 속도가 향상되지만 이에 비례하여 안정성이 떨어지게 된다. 소음원 입력의 파워가 시변 할 경우 적응 알고리즘의 안정성이 약화되는 문제점이 발생하는데, 본 논문에서는 Leaky LMS알고리즘과 비슷한 구조이지만 안정성이 강화된 IIR정규화 LMS 알고리즘을 제안한다. 제안한 알고리즘의 유용성을 비교 분석하기 위하여 실험을 수행하였다.

• Journal of Korea Society of Industrial Information Systems
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• v.5 no.2
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• pp.32-38
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• 2000

One of the most popular algorithm in adaptive signal processing is the least mean square(LMS) algorithm. The majority of these papers examine the LMS algorithm with a constant step size. The choice of the step size reflects a tradeoff between misadjustment and the speed of adaptation. Subsequent works have discussed the issue of optimization of the step size or methods of varying the step size to improve performance. However there is as yet no detailed analysis of a variable step size algorithm that is capable of giving both the adaptation speed and the convergence. In this paper we propose a new variable step size algorithm where the step size adjustment is controlled by the gradient of error square. The proposed algorithm is performed in the Walsh-Hadamard domain in real-valued orthogonal transform because of fast convergence. The simulation results using the new algorithm for noise canceller system is described. They are compared to the results obtained by other algorithms. It is shown that the proposed algorithm produces good results compared with conventional algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.8
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• pp.745-757
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• 1991

In this paper, the theoretical convergence property of the individual tap LMS algorithm for equaliz action if analyzed, and the pefomances over seeral multipath time vaing mobile radio channels are investigaed. The individual tap adjusting method of the tapped-elay line equalizer using LMS algorithm is proved to have Wiener optimum solution. It has more rapid convergence speed and lowe bit error rates than conventional Tdl LMS and gradient lattice equlizer in time invariant or time variant multipath channels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.3C
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• pp.183-189
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• 2011

The LMS(Least Mean Square) algorithm is generally used because of tenacity, high mating spots and simplicity of realization. But the LMS algorithm has trade-off between nonuniform collect and EMSE(Excess Mean Square Error). To overcome this weakness, variable step size is used widely but it needs a lot of calculation load. In this paper we consider new algorithm, which can reduce calculations and adapt in case of environment changes, uses original signal and noise signal of IGC(Instantaneous Gain Control). For the real time processing of IGC algorithm, we remove the logarithmic function. The performance of proposed algorithm is tested to adaptive noise canceller in automobile. We show implemented LabVIEW FPGA system of IGC algorithm is more efficient than others.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.10C
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• pp.1007-1012
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• 2003

In order to accelerate the convergence speed of the conventional BP algorithm, constrained optimization techniques are applied to the BP algorithm. First, the noise-constrained least mean square algorithm and the zero noise-constrained LMS algorithm are applied (designated the NCBP and ZNCBP algorithms, respectively). These methods involve an important assumption: the filter or the receiver in the NCBP algorithm must know the noise variance. By means of extension and generalization of these algorithms, the authors derive an adaptive error-constrained BP algorithm, in which the error variance is estimated. This is achieved by modifying the error function of the conventional BP algorithm using Lagrangian multipliers. The convergence speeds of the proposed algorithms are 20 to 30 times faster than those of the conventional BP algorithm, and are faster than or almost the same as that achieved with a conventional linear adaptive filter using an LMS algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.11
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• pp.1714-1725
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• 1993

This paper analyzes the properties of such algorithm that corresponds to the nonlinear adaptive algorithm with additional update terms, parameterized by the scalar factors a1, a2, a3 and Presents its structure. The analysis of convergence leads to eigenvalues of the transition matrix for the mean weight vector. Regions in which the algorithm becomes stable are demonstrated. The time constant is derived and the computational complexities of MLMS algorithms are compared with those of the conventional LMS, sign, LFG, and QFG algorithms. The properties of convergence in the mean square are analyzed and the expressions of the mean square recursion and the excess mean square error are derived. The necessary condition for the CFG algorithm to be stable is attained. In the computer simulation applied to the system identification the CFG algorithm has the more computation complexities but the faster convergence speed than LMS, LFG and QFG algorithms.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.3
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• pp.130-135
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• 2006

There have been experiments dealing with the possibility of the actualization of the ANC system by means of operating the DSP adaptation filter. This filter is composed of various filters(including X-LMS algorithm, Filter-U algorithm, and Full-Feedback-Filter-U algorithm) that use ventilation fans and loudspeakers as a primary source in a circular duct as an experimental device. In this operation, the ANC system using the X - LMS algorithm was found to be more effective in reducing noise than without such system. When applying the input signal of the DSP board Full Feedback-Filtered-U algorithm system while having in mind that the additionally installed second control signal was gone through feedback and mixed into the detection microphone installed near the ventilation fan when using the first ventilation fan, the system was not emitted, but maintained stable during the operation of the control filter. At this point, noise tended to decrease at a maximum of l0dB compared to other algorithms at the frequency band of 170-250Hz.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.9
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• pp.1058-1064
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• 2008

In this paper, we proposed a new hybrid interference canceller using the adaptive filter with Grouped CMA(Constant Modulus Algorithm)-LMS(Least Mean Square) algorithm in the RF(Radio Frequency) repeater. The feedback signal generated from transmitter antenna to receiver antenna reduces the performance of the receiver system. The proposed interference canceller has better channel adaptive performance and a lower MSE(Mean Square Error) than conventional structure because it uses the cancellation method of Grouped CMA algorithm. This structure reduces the number of iterations fur the same MSE performance and hardware complexity compared to conventional nonlinear interference canceller. Namely, MSE values of the proposed algorithm were lower than those of LMS algorithm by 2.5 dB and 4 dB according to step sizes. And the proposed algorithm showed fast speed of convergence and similar MSE performance compared to VSS(Variable Step Size)-LMS algorithm.