• 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.

• Journal of Korea Multimedia Society
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• v.11 no.8
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• pp.1051-1058
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• 2008

The advancement of technology for image processing and communications makes it possible for current traffic signal controllers and vehicle detection technology to make both emergency vehicle preemption and transit priority strategies as a part of integrated system. Present]y traffic signal control in crosswalk is controlled by fixed signals. The signal control keeps regular signals traffic even with no traffic, when there is traffic, should wait until the signal is given. Waiting time causes the risk of traffic accidents and traffic congestion in accordance with signal violation. To help reduce the risk of accidents and congestion, this paper explains traffic signal control system for the adaptive priority order so that signal may be preferentially given in accordance with the situation of site through the object detect images.

• JSTS:Journal of Semiconductor Technology and Science
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• v.13 no.6
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• pp.608-616
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• 2013

This paper presents an adaptive sampling method for electrocardiogram (ECG) signal detection. First, by employing the strings matching process with compression dictionary, we recognize each segment of ECG with different characteristics. Then, based on the non-uniform sampling strategy, the sampling rate is determined adaptively. As the results of simulation indicated, our approach reconstructed the ECG signal at an optimized sampling rate with the guarantee of ECG integrity. Compared with the existing adaptive sampling technique, our approach acquires an ECG signal at a 30% lower sampling rate. Finally, the experiment exhibits its superiority in terms of energy efficiency and memory capacity performance.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.7
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• pp.83-91
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• 1993

A ghost cancelling method using the multiplicationless adaptive multipath channel identification is proposed. The IIR filter and the LMS algorithm are used for ghost cancelling. The coefficients of IIR filter are obtained by multipath channel identification. The LMS algorithm which is simple relatively is used as the adaptive algorithm. An MPS is selected as the reference signal and it is used as the input of the adaptive algorithm for the multipath channel identification. If an MPS is not exist, the horizontal syne, and color burst signal can be used as the reference signal. Improving of accuracy of the ghost cancelling in the presence of the phase variation in the multipath channel, a complex processing are also performed.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.179-182
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• 2002

In this paper, we propose a wavelet based adaptive algorithm which improves the convergence speed and reduces computational complexity using the fast running FIR filtering efficiently We compared the performance of the proposed algorithm with time and frequence domain adaptive algorithm using computer simulation of adaptive noise canceler based on synthesis speech. As the result, the proposed algorithm is suitable for adaptive signal processing area using speech or acoustic field.

• Journal of Satellite, Information and Communications
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• v.10 no.4
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• pp.136-140
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• 2015

In this paper, a comparative studies on the STAP and SFAP were performed, which are known as representative anti-jamming technology for adaptive array antenna. As a method of estimating the weighting vector for simulation, MMSE(Minimum Mean Square Error) algorithm was commonly used and the analyses of the simulation performance in various jamming environments were presented. Especially, performance comparison between STAP and SFAP according to the jamming power J/S(Jamming to Signal Power Ratio), performance comparison in the ratio of jamming bandwidth to signal bandwidth, and performance comparison of BER between STAP and SFAP were presented.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.1
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• pp.45-50
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• 2019

When PPG signal is used in mobile healthcare devices, the accuracy of the measured heartbeat decreases from the influence by the movement of the user. The reason is that the frequency band of the noise overlaps the frequency band of the PPG signal. In order to remove these same noises, the methods using frequency analysis method or application of acceleration sensor have been investigated and showed excellent performance. However, in applying these methods to low-cost healthcare devices, it is difficult to apply these methods because of much processing time and sensor's cost. In order to solve these problems, this study proposed the filter design method using an adaptive notch filter and the fuzzy inference system to extract more accurate heart rate in real time and evaluated its performance. As results, it showed better results than the other methods. Based on the results, when applying the proposed method to design the mobile healthcare device, it is possible to measure the heartbeat more accurately in real time.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.889-890
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• 2006

This paper pertains to introducing the design of adaptive filters for the cancellation of muscle noise among several types of noise sources from the ECG signal. We used EMG signals measured along with ECG at the same time to use it as the reference input to the adaptive filter for the experiments. PSD results showed that the statistical characteristics of ECG are closely correlated with those of EMG.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3559-3571
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• 2015

This paper addresses the problem of signal acquisition with a sparse representation in a given orthonormal basis using fewer noisy measurements. The authors formulate the problem statement for randomly measuring with strong signal noise. The impact of white Gaussian signals noise on the recovery performance is analyzed to provide a theoretical basis for the reasonable design of the measurement matrix. With the idea that the measurement matrix can be adapted for noise suppression in the adaptive CS system, an adapted selective compressive sensing (ASCS) scheme is proposed whose measurement matrix can be updated according to the noise information fed back by the processing center. In terms of objective recovery quality, failure rate and mean-square error (MSE), a comparison is made with some nonadaptive methods and existing CS measurement approaches. Extensive numerical experiments show that the proposed scheme has better noise suppression performance and improves the support recovery of sparse signal. The proposed scheme should have a great potential and bright prospect of broadband signals such as biological signal measurement and radar signal detection.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.1-4
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• 2001

In this paper, we develop a blind adaptive multiuser detector for synchronous CDMA with a noise-whitened filter. To Improve the symbol error probability performance, Decision-Feedback Blind Adaptive Multiuser Detector(DFBD) is proposed and compared with Blind Adaptive Multiuser Detector(BD). The proposed DFBD is slightly improved.