• The Journal of the Acoustical Society of Korea
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• v.15 no.5
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• pp.21-29
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• 1996

Industrial equipment, such as power plant, is required to operate reliably, continuously and economically under rather severe conditions of temperature, stress, and enbironment. To test structural integrity and fitness, ultrasonic nondestructive testing is used because of effectiveness and simplicity. In this paper, wavelet transform based least mean square(LMS) algorithm is applied to reduce the influence of the interference occurring between randomly positioned small scatters. The RUN test is performed to check the nonstationarity of the speckle noise signal. The performance of this new approach is compared with that of the time domain LMS algorithm by means of condition numbers, signal-to-noise ratio and 3-D image. As a result, the wavelet transform based LMS algorithm shows better performance than the time domain LMS algorithm in this experiment.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.1016-1019
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• 2004

The study of the noise reduction of an automobile has been concentrated on the reduction of the automotive engine noise because the engine noise is the major cause of automotive noise. However, many studies of automotive engine noise led to the interest of the noise reduction of the exhaust and intake system. The method of the reduction of the induction noise can be classified by the method of passive control and the method of active control. However, the passive control method has a demerit to reduce the effect of noise reduction at low frequency (below 500Hz) range and to be limited by a space of the engine room. Whereas, the active control method can overcome the demerit of passive control method. The algorithm of active control is mostly used the LMS (Least-Mean-Square) algorithm because the LMS algorithm can easily obtain the complex transfer function in real-time. Especially, Filtered-X LMS (FXLMS) algorithm is applied to an ANC system. However, the convergence performance of LMS algorithm goes bad when the FXLMS algorithm is applied to an active control of the induction noise under rapidly accelerated driving conditions. So, in order to this problem, the modified FXLMS algorithm using Moving Bandpass Filter was proposed. In this study, MBPF was implemented and use ANC for automotive intake under revived rapidly accelerated driving conditions and it was verified its performance.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.6
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• pp.1-10
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• 2019

This paper proposes a method to improve the detectable distance by reducing noise to perform a signal processing technique on the received signals. To increase the radar detection range, the noise component of the received signal has to be reduced. The proposed method reduces the noise component by employing two methods. First, the radar signals received with multiple pulses are accumulated. As the number of additions increases, the noise component gradually decreases due to noise randomness. On the other hand, the signal term gradually increases and thus signal to noise ratio increases. Secondly, after converting the accumulated signal into the frequency spectrum, a Least Mean Square (LMS) filter is applied. In the case of the radar received signal, desired signal exists in a specific part and most of the rest is a noise. Therefore, if the LMS filter is applied in the time domain, the noise increases. To prevent this, the LMS filter is applied after converting the received signal into the entire frequency spectrum. The LMS filter output is then transformed into the time domain and then range estimation algorithm is performed. Simulation results show that the proposed scheme reduces the noise component by about 25 dB. The experiment was conducted by comparing the proposed results with the conventional results of the radars held by the Korea Aerospace Research Institute for the international space station.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.673-682
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• 2004

The adaptive beam-forming is promising approach for noise reduction in hearing aids. This approach has come in the focus of interest only recently, because of the availability of new and powerful digital signal processors. The adaptation U using usually a Least Mean Squares algorithm, updates the weight vector. In this Paper, we propose a fast wavelet based adaptive algorithm using variable step size algorithm which varies adaptive constant by the change of signal environment. We compared the performance of the proposed algorithm with the known adaptive algorithm using computer simulation of multi channel adaptive bemformer in hearing aids. As the result the proposed algorithm is suitable for adaptive signal processing area using hearing aids and has advantages reducing computational complexity. And we show the beam-forming system using proposed algorithm converges stably in a sudden change of system environment.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.69-72
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• 1999

In this paper, an efficient time domain equalization algorithm for discrete wavelet multitone(DWMT) data transmission is developed. In this algorithm, the time domain equalizer(TEQ) consists of two stages, i.e., the channel impulse response shortening equalizer(TEQ-S) in the first stage and the channel frequency flattening equalizer(TEQ-F) in the second stage. TEQ-S reduces the length of transmission channel impulse response to decrease intersymbol interference(ISI) followed by TEQ-F that enhances the channel frequency response characteristics to the level of an ideal channel, hence diminishes the bit error rate. TEQ-S is implemented using the least-squares(LS) method, while TEQ-F is designed by using the least mean-square(LMS) algorithm. Since DWMT system also requires of the frequency domain equalizer in order to further reduce ICI and ISI the hardware complexity is an another concern. However, by adopting an well designed and trained TEQ, the hardware complexity of the whole DWMT system can be greatly reduced.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.1
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• pp.19-25
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• 2007

The MFC(Mass Flow Controller) is an equipment that measures and controls mass flow rates of fluid. Most of the HFC system is still using the PID algorithm. The PID algorithm shows superior performance on the MFC system. But the PID algorithm in the MFC system has a few problems as followed. The characteristic of the MFC system is changed according to the operating environment. And, when the piezo valve that uses the control valve is assembled in the MFC system, a coupling error is generated. Therefore, it is very difficult to find out the exact parameters of MFC system. In this paper, we propose adaptive PID algorithm in order to compensate these problems of a traditional PID algorithm. The adaptive PID algorithm estimates the parameters of MFC system using LMS(Least Mean Square) algorithm and calculates the coefficients of PID controller. Besides, adaptive PID algorithm shows better transient response because adaptive PID algorithm includes a feedforward. And we implement MFC system using proposed adaptive PID algorithm with self-tuning and Ziegler and Nickels's method. Finally, comparative analysis of the proposed adaptive PID and the traditional PID is shown.

• Journal of Korea Multimedia Society
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• v.8 no.8
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• pp.1051-1056
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• 2005

Least mean square(LMS) algorithm is 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, we use adaptive algorithm of wavelet transform. And we propose a new wavelet based adaptive algorithm of wavelet transform. And we propose a new 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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.4
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• pp.453-461
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• 2011

In order to use more efficiently limited frequency resources at the broadcasting band and to eliminate blanket area of the terrestrial broadcasting and to improve broadcasting quality. The importance of repeaters has increasing continuously. However, in case of T-DMB digital on channel repeater in OFDM systems, some of the signal radiated feedback again at the receiver antenna. So it generates feedback signal interference in repeater system. Also phase noise increases ICI(Inter Carrier Interference). It affects seriously the frequency domain equalizer. In this paper, we remove the feedback signal interference by LMS with correlation. Also we propose an effective equalizer algorithm that can remove ICI caused by phase noise and the power amplifier's back-off. In this simulation results, this system is satisfied the performance of BER=$10^{-4}$ at less than SNR=14 dB after compensation of phase noise.

• The Journal of the Acoustical Society of Korea
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• v.32 no.5
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• pp.408-414
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• 2013

The famous filtered-x least mean square (FxLMS) algorithm for active noise control (ANC) systems may become unstable in non-stationary noise environment. To solve this problem, Sun's algorithm and Akhtar's algorithm are developed based on modifying the reference signal in update of FxLMS algorithm, but these two algorithms have dissatisfactory stability in dealing with sustaining impulsive noise. In proposed algorithm, probability estimation and zero-crossing rate (ZCR) control are used to improve the stability and performance, at the same time, an optimal parameter selection based on fuzzy system is utilized. Computer simulation results prove the proposed algorithm has faster convergence and better stability in non-stationary noise environment.

• 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.