• The Journal of the Acoustical Society of Korea
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• v.36 no.1
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• pp.57-63
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• 2017

This paper presents an active acoustic-reflection control algorithm based on a single sensor. The proposed algorithm operates in a system comprising a single sensor located nearby the reflective surface and a control transducer mounted on the reflective surface. First, the incident and reflected acoustic signals are separated from the sensor signal, and a control signal is generated using the separated signals. For the signal separation, the proposed algorithm requires the response of the reflection path which is estimated from the acoustic response between an external sound source and the sensor. Finally, the control filter is adjusted using the FxLMS (Filtered-x Least Mean Square) algorithm. To verify the effectiveness of the proposed algorithm, it was implemented in real time using a DSP (Digital Signal Processing) board, and the experimental results obtained in one-dimensional air-acoustic environment show that the reflections of the 1 kHz burst can be reduced by 11.6 dB.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8C
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• pp.801-805
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• 2006

A normalization approach to coefficient adaptation in the escalator(ESC) filter structure that conventionally employs least mean square(LMS) algorithm is introduced. Using Taylor's expansion of the local error signal, a normalized form of the ESC-LMS algorithm is derived. Compared with the computational complexity of the conventional ESC-LMS algorithm employs input power estimation for time-varying convergence coefficient using a single-pole low-pass filter, the computational complexity of the proposed method can be reduced by 50% without performance degradation.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.3
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• pp.600-607
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• 2007

In the next generation mobile multimedia communications, the broad band shot-burst transmissions are used to reduce end-to-end transmission delay, and to limit the time variation of wireless channels over a burst. However, training overhead is very significant for such short burst formats. So, the availability of the short training sequence and the fast converging adaptive algorithm is essential in the system adopting the symbol-by-symbol adaptive equalizer. In this paper, we propose an adaptive equalizer using the DWMT (discrete multi-wavelet transform) and LMS (least mean square) adaptation. The proposed equalizer has a faster convergence rate than that of the existing transform-domain equalizers, while the increase of computational complexity is very small.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.3
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• pp.158-163
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• 2009

LMS(Least Mean Square) algorithm requires simple equation and is used widely because of the low complexity. If the convergence speed increase, LMS algorithm has a divergence in case of sharp environment changes. And if a stability increase, the convergence speed becomes slow. This algorithm based on a trade off between fast convergence and system stability. To improve this problem, VSSLMS (Variable Step Size LMS) algorithm was developed. The VSSLMS algorithm improved the convergence speed and performance as adjusting step size using error signal. In this paper, I-VSSLMS algorithm is proposed tor improve the performance of adaptive noise canceller in real-time environments. The proposed algorithm is applied to adaptive noise canceller using TMS320C6713 DSP board and we did simulation by real time. Then we compared performance of each algorithm and demonstrated that proposed algorithm has superior performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.6
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• pp.1095-1106
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• 1994

This paper presents a method for determining optimal grayscale function processing(FP) morphological filters under the least square (LMS) error criterion. The optimal erosion and dilation filters with a grayscale structuring element(GSE) are determined by minimizing the mean square error (MSE) between the desired signal and the filter output. It is shown that convergence of the erosion and dilation filters can be achieved by a proper choice of the step size parameter of the LMS algorithm. In an attempt to determine optimal closing and opening filters, a matrix representation of both opening and closing with a basis matrix is proposed. With this representation, opening and closing are accomplished by a local matrix operation rather than cascade operations. The LMS and back-propagation algorithm are utilzed for obtaining the optimal basis matrix for closing and opening. Some results of optimal morphological filters applied to 2-D images are presented.

• Journal of Communications and Networks
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• v.7 no.3
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• pp.243-247
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• 2005

We propose an efficient block least-mean-square (BLMS) adaptive algorithm, in conjunction with error control coding, for direct-sequence code division multiple access (DS-CDMA) systems. The proposed adaptive receiver incorporates decision feedback detection and channel encoding in order to improve the performance of the standard LMS algorithm in convolutionally coded systems. The BLMS algorithm involves two modes of operation: (i) The training mode where an uncoded training sequence is used for initial filter tap-weights adaptation, and (ii) the decision-directed where the filter weights are adapted, using the BLMS algorithm, after decoding/encoding operation. It is shown that the proposed adaptive receiver structure is able to compensate for the signal-to­noise ratio (SNR) loss incurred due to the switching from uncoded training mode to coded decision-directed mode. Our results show that by using the proposed adaptive receiver (with decision feed­back block adaptation) one can achieve a much better performance than both the coded LMS with no decision feedback employed. The convergence behavior of the proposed BLMS receiver is simulated and compared to the standard LMS with and without channel coding. We also examine the steady-state bit-error rate (BER) performance of the proposed adaptive BLMS and standard LMS, both with convolutional coding, where we show that the former is more superior than the latter especially at large SNRs ($SNR\;\geq\;9\;dB$).

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.3
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• pp.169-174
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• 2015

Noise problem that occurs on the road is raising a lot of problems in the economic, social and environmental aspects. The active noise control (ANC) systems based on the filtered-X least mean square(FxLMS) algorithm have a problem with compensating the acoustic feedback of secondary route. However, newly proposed correlation-LMS(CLMS) and expanded CLMS algorithms have slightly much calculation and are minutely behind performance, these have a advantage not in measuring transfer function onerously so that we can easily adapt these in real time. The CLMS and expanded CLMS algorithm was developed to improve the real-time implementation performance under the variable input noise such as road noise environment. In this paper, we compared and analyzed their performance. From the results of the Matlab simulation for an ANC system, it is shown that expanded CLMS algorithms are more convergence speed and keep the desirable performance even in the input of road noise situation.

• The Journal of the Acoustical Society of Korea
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• v.17 no.3E
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• pp.43-46
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• 1998

Many of the active noise control system utilize a form of the least mean square(LMS) algorithm. This paper discusses the dependence of the convergence rate on the acoustic error path in the popular algorithm which is conventional "filtered-x LMS" and introduces new algorithm "constrained filtered-x LMS". The proposed method increase the convergence region regardless of the time-delay in the acoustic error path. In the algorithms, coefficients of the controller are adapted using the residuals of constrained structure which are defined in such a way that the control process become stationary. Advantages of constrained filtered-x LMS algorithm is illustrated by convergence analysis in the mean sense.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.565-567
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• 2004

In active noise control (ANC) systems, the convergence behavior of the conventional Filtered-X Least Mean Square (FXLMS) algorithm may be affected by nonlinear distortions in the secondary path (e.g., in the power amplifiers, loudspeakers, transducers, etc.), which may lead to degradation of the error-reduction performance of the ANC systems. In this paper, a stable FXLMS algorithm with fast convergence is proposed to compensate for undesirable nonlinear distortions in the secondary-path of ANC systems by employing the Volterra filtering approach. In particular, the proposed approach is based on the utilization of the conventional P-th order inverse approach to nonlinearity compensation in the secondary path of ANC systems. Finally, the simulation results showed that the proposed approach yields a better convergence behavior In the nonlinear ANC systems than the conventional FXLMS.