• Journal of the korean Society of Automotive Engineers
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• v.14 no.5
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• pp.95-106
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• 1992

Active control of acoustic noise is an application area of adaptive digital signal processing with increasingly interest along the last year. This work studies the implementation of the multichannel LMS filter and the application of this algorithm for the reduction of the noise inside a vechicle cabin using a number of 'secondary sources' drived by adaptive filtering of a reference noise source. Firstly, we propose the use of an adaptive method for the time-varient optimal convergence factor. Secondly, we propose the use of adaptive delayed inverse model to estimate the elastic-acoustic transfer function presented in vechicle cabin. The original, primary source is often periodic, with a known fundamental frequency. A suitably filtered reference signal can thus be used to drive the secondary sources. An algorithm is presented for adapting the coefficients of an FIR filter feeding such a secondary source in such a way as to minimize the output of a suitably placed microphone. In this algorithm, the coefficients of adaptive filter driving an array of secondary sources can be adapted to minimize the sum of the squares of the outputs of a number of error microphones. The multichannel LMS algorithm displays that such an algorithm is considered suitable to used for the global suppression of noise in vehicle cabin.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.804-806
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• 2014

During the transmission process of processing of image, various noises are added causing an error to the image. In order to restore these images, methods such as alpha trimmed average filter, standard median filter and switching median filter were proposed but such previous methods has insufficient noise suppression characteristics. Therefore in this paper, in order to remove the impulse noise added to the image, an adaptive median filter algorithm modified to expand the mask according to the noise density of mask pixels was proposed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.2
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• pp.239-247
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• 2018

Adaptive Beamforming (ABF) algorithm, which is a typical jammer suppression algorithm, guarantees the performance on the assumption that the jamming characteristics of the TDS (Training Data Sample) are stationary, which are obtained immediately before and after transmitting the pulse signal. Therefore, effective jammer suppression can not be expected when the jamming characteristics are non-stationary. In this paper, we propose a new jammer suppression algorithm, of which power spectrum fluctuates fast. In this case, we assume that the location of the jammer station is fixed during the processing time. By applying the MPM (Matrix Pencil Method) to the jamming signal in TDS, we can estimate jammer parameters such as power and incident angle, of which the power will vary fast in time or range bins after TDS. Though we assume that the jammer station is fixed, the estimated jammer's incident angle has an error due to the noise, which degrades the performance of the jammer suppression as the jammer power increases fast. Therefore, the jammer's incident angle should be re-estimated at each range bin after TDS. By using the re-estimated jammer's incident angle, we can construct new covariance matrix under the non-stationary jamming environment. Then, the optimum weight for the jammer suppression is obtained by inversing matrix estimation method based on the matrix projection with the estimated jammer parameters as variables. To verify the performance of the proposed algorithm, the SINR (signal-to-interference plus noise ratio) loss of the proposed algorithm is compared with that of the conventional ABF algorithm.

• 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).

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.69-74
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• 1999

Adaptive algorithms based on gradient adaptation have been extensively investigated and successfully joined with active noise/vibration control applications. The Filtered-X LMS algorithm became one of the basic feedforward algorithms in such applications, but is not fully understood yet. Effects of cancellation path model on the Filtered-X LMS algorithm have investigated and some useful properties related to stability were discovered. Most of the results stated that the error in the cancellation path model is undesirable to the Filtered X LMS. However, we started convergence analysis of Filtered-X LMS based on the assumption that erroneous model does not always degrade its performance. In this paper, we present a way of optimizing the cancellation path modern in order to enhance the convergence speed by introducing intentional phase error. Carefully designed intentional phase error enhances the convergence speed of the Filtered X LMS algorithm for pure tone noise suppression application without any performance loss at steady state.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.34-42
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• 2010

The DOA(direction of arrival), which is based on parametric and nonparametric estimation algorithm, and adaptive beamforming algorithm for mobile communication environments are researched and analyzed. In parametric estimation algorithm, eigenvalues of the signal component and the noise component are obtained from correlation matrix of received signal by array antenna and power spectrum of the received signal is discriminated from them. Otherwise, in nonparametric estimation algorithm, we minimize a regularized objective function for finding a estimate of the signal energy as a function of angle, using nonquadratic norm which leads to supper resolution and noise suppression. And then, DOA is estimated by the signal and noise spatial steering vector, and adaptive beam-forming pattern is improved by weight vectors obtained from the spatial vector. Therefore, the improved directional estimation algorithm with regularizing sparsity constraints offers super-resolution and noise suppression compared to other algorithms.

• Communications for Statistical Applications and Methods
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• v.18 no.6
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• pp.871-886
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• 2011

This paper proposes a powerful SVM-ASM filter, the adaptive switching median(ASM) filter based on support vector machines(SVMs), to effectively reduce impulse noise in corrupted images while preserving image details and features. The proposed SVM-ASM filter is composed of two stages: SVM impulse detection and ASM filtering. SVM impulse detection determines whether the pixels are corrupted by noise or not according to an optimal discrimination function. ASM filtering implements the image filtering with a variable window size to effectively remove the noisy pixels determined by the SVM impulse detection. Experimental results show that the SVM-ASM filter performs significantly better than many other existing filters for denoising impulse noise even in highly corrupted images with regard to noise suppression and detail preservation. The SVM-ASM filter is also extremely robust with respect to various test images and various percentages of image noise.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.3A
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• pp.179-187
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• 2012

In this paper, we propose an adaptive DFE (Decision Feedback Equalizer) based on LDPC (Low Density Parity Check) code for phase noise suppression and performance improvement. The proposed equalizer in this paper is applied for wireless repeater system. So as to meet ever increasing requirements on higher wireless access data rate and better quality of service (QoS), the wireless repeater system has been studied. The echo channel and RF impairments such as phase noise produce performance degradation. In order to remove echo channel and phase noise, we suggest a novel adaptive DFE equalizer based on LDPC code. The proposed equalizer helps to compensate RF impairments and improve the performance significantly better than used independently. In addition, proposed equalizer has less iteration number of LDPC code. So, the proposed equalizer system has low complexity.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.4
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• pp.267-275
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• 2004

This research is concerned with the development of a real-time adaptive PPF controller for the active vibration suppression of smart structure. In general, the tuning of the PPF controller is carried out off-line. In this research, the real-time learning algorithm is developed to find the optimal filter frequency of the PPF controller in real time and the efficacy of the algorithm is proved by implementing it in real time. To this end, the adaptive algorithm is developed by applying the gradient descent method to the predefined performance index, which is similar to the method used popularly in the optimization and neural network controller design. The experiment was carried out to verify the validity of the adaptive PPF controller developed in this research. The experimental results showed that adaptive PPF controller is effective for active vibration control of the structure which is excited by either impact or harmonic disturbance. The filter frequency of the PPF controller is tuned in a very short period of time thus proving the efficiency of the adaptive PPF controller.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.302-307
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• 2001

This research is concerned with the development of a real-time adaptive PPF controller for the active vibration suppression of smart structure. In general, the tuning of the PPF controller is carried out off-line. In this research, the real-time learning algorithm is developed to find the optimal filter frequency of the PPF controller in real time and the efficacy of the algorithm is proved by implementing it in real time. To this end, the adaptive algorithm is developed by applying the gradient descent method to the predefined performance index, which is similar to the method used popularly in the optimization and neural network controller design. The experiment was carried out to verify the validity of the adaptive PPF controller developed in this research. The experimental results showed that adaptive PPF controller is effective for active vibration control of the structure which is excited by either impact or harmonic disturbance. The filter frequency of the PPF controller can be tuned in a very short period of time thus proving the efficiency of the adaptive PPF controller.