• The Journal of the Acoustical Society of Korea
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• v.34 no.2
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• pp.130-137
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• 2015

In this paper, we propose a new Modified Filtered-x Affine Projection Sign Algorithm(MFxAPSA) to improve the convergence speed of the conventional MFxAPSA which has been proposed for active control of impulsive noise. Under the impulsive noise environment, the adaptive algorithms based on the second order moment such as the Filtered-x Least Mean Square(FxLMS) show slow convergence speed or diverge because the noise source tends to have infinite variance. The MFxAPSA is the algorithm derived by applying the Affine Projection Sign Algorithm(APSA) to active noise control. The APSA has an advantage that it does not need the calculation for the inverse matrix, so it may be suitable for the active noise control that requires low computational burden. The proposed MFxAPSA also has APSA's advantage and furthermore, better performance than the conventional MFxAPSA. We carried out a performance comparison of the proposed MFxAPSA with the conventional MFxAPSA. It is shown that the proposed MFxAPSA has the faster convergence speed than the conventional MFxAPSA.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.3
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• pp.119-128
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• 2005

In this paper, an robust adaptive backstepping controller is proposed for the chaos system with disturbances. This controller will be applicable to the chaos system of strict-feedback form and utilize the saturation function for decreasing the effect of disturbances derived from unmodelled dynamics and external noise. It shows that backstepping algorithm can be used to solve the problems of nonlinear system very well and robust controller can be designed without the variation of adaptive law. Simulation results are provided to demonstrate the effectiveness of the proposed controller.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.6B
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• pp.1092-1099
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• 2000

An adaptive array system can effectively remove all received interferences by using adaptive algorithms even though the received signal condition is not known. The conventional adaptive array systems, however, cannot remove all interferences adaptively and converge very slowly when the eigenvalue spread of the input covariance matrix is large. In the paper, a new adaptive array system called an automatic gain controller (AGC) Applebaum array and its control algorithm are proposed to overcome the performance degradation of conventional Applebaum array in multiple interference conditions. The performance analysis of the proposed AGC Applebaum array is described under the condition of multiple narrowband interferences. Simulation results show the array output signal-to-noise ratio (SNR) of the AGC Applebaum array increases by 30dB compared to that of the conventional Applebaum array in the simulation condition. The gain of the AGC Applebaum array in the incident direction of a weaker interference is also shown to be lower than that of the conventional Applebaum array.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.182-187
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• 1992

This paper proposes a method by which the estimated values of the unknown parameters of system are converged to the true values in finite time using adaptive deadbeat controller. After those are converged to the true values, the deviation from these values do not virtually exist or, if any, extremely small. Also we apply this technique of deadbeat convergence to a system contaminated with white noise or colored noise. It is shown that the estimated parameters of those systems approach the true values in finite time even though the performance do not match perfectly with the system without noises.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.377-380
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• 2002

When it calculates the optimum price of filter coefficient, the many operation quantity is necessary. Is like that the real-time control is difficult and the hardware embodiment expense is big. The case which does not know advance information of input signal or the case where the statistical nature changes with change of surroundings environment is necessary the adaptive filter. Every hour to change a coefficient automatically and system in order to reach to the condition of optimum oneself, the fact that is the adaptive filter. When it does not the quality of input signal or it does not know the environment of surroundings every hour changing, it does not emit not to be, in order to collect, the fact that is the adaptive filter. The case of the Acoustic Echo Canceler does thousands filter coefficients in necessity. It reduces a many calculation quantity to respect, it uses the IIR filter from hour territory. Also it uses the block adaptive filter which has a block input signal and a block output signal. The former there is a weak point where the stability discrimination is always demanded. Consequently, The block adaptive filter is researched plentifully. This dissertation planned the block MADF adaptive filter used to MADf algorithm.

• 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 ($SNR\;\geq\;9\;dB$).

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.54.4-54
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• 2002

1.Introduction 2. Channel Equalizer Using Adaptive Neural Network 3. Data Modulation and Demodulation Using Haar Transform 4. Binary Signal Transmission Using Haar Transform 5. Conclusion

• Journal of the Korean Society for Precision Engineering
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• v.14 no.3
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• pp.107-113
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• 1997

This paper presents the active control of a flexible cantilever beam vibration. The cantilever beam was excitied by a steady-state harmonic and white noise point force and the control was performed by one piezo ceramic actuator bonded to the surface of the beam. An adaptive controller based on filtered-x LMS algorithm was used and the controller was defined by minimizing the square of the response of error sensor. In the experiment, gap sensor was used as an error sensor while the sinusoidal or white noise was applied as a disturbance. In the case of sinusoidal input, more than 20 dB of vibration reduction was achieved over all range of the natural frequencies and it takes 5 seconds to control the vibration at first natural frequency and 1 second at other natural frequencies. In the case of white noise input, 7 dB of vibration reduction was achieved at the first natural frequency and good control performance was achieved in the considered whole frequency range. Results indicate that the vibration of a flexible cantilever beam could be controlled effectively when the piezo ceramic actuator was used with filtered-x LMS algorithm.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1327-1329
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• 1996

This paper presents an active noise control (ANC) algorithm using orthogonalization property of Walsh transform. Conventional ANC algorithm known as filtered-x LMS(FXL) algorithm has a problem of decreasing convergence speed in FIR adaptive filters operating in colored noise environments. Walsh transform decompose an input signal into a set of N uncorrelated components and reduce eigenvalue spread of autocorrelation matrix of input sequences. Computer simulations show that proposed (FXW) algorithm is superier to FXL in convergence speed.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.11
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• pp.503-510
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• 1986

A new algorithm based on the concept of prediction error minimization is suggested to estimate the time varying delay in discrete processes. In spite of the existence of the stochastic noise, this algorithm can estimate time varying delay accurately. Computation time of this algorithm is far less than that of the previous extended parameter methods. With the use of this algorithm, generalized minimum variance control shows good control behavior in simulations.