• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.971-974
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• 2001

Multi-Carrier Spread Spectrum communications has shown the ability of transform domain excision using the wavelet transformation to improve system performance when transmitting signals in the presence of additive white Gaussian noise and interference. In such work, the transforms were implemented using FIR filters and IIR filter. Some well-known classes of sequences, such as Pseudo noise, Walsh, Cold sequences are evaluated with respect to the basic criteria. The main objective is to implement the wavelet transform using IIR filters. This filters are well known to have sharper transition regions leading to better performance. Numerical simulation of multi-carrier spread spectrum communication systems have shown that IIR filters are better in removing the sinusoidal jammer and subsequently yield better BER performance.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.12
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• pp.20-26
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• 1994

Lossless system has been employed to design the perfect reconstruction filter banks and has particularly a close relation with the desing of orthogonal wavelet filter (OWF). With such a relation, we generalize 2-band OWF to the M-band OWF which has an improved performances. The improvement is achieved using the two techniques. One is that the wavelet low pass filter has (N-1)th order regularity with extra zeros while the existing filter has N-th order regularity. The other is that unitary matrix is designed by adding the zeros to the proper positions. As a result, M-band OWF designed by propose method has better performance than M-band OWF designed by exsiting method.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.102-105
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• 2003

Up to the present studies of the car number recognition system, it is generally known to have serious problems such as relatively long processing time due to the excessive length of data extracted from the number plate based on the current image characteristics, and the image blurring with the physical damage of the brightness and darkness signals of the number plate caused by external impulses with many difficulties in the extraction of the highlighted numbers. In this Paper we used the characteristics firstly having a constant brightness of number plate, and a high density to the horizontal axis, and the influences of highlighted signal could be reduced by making reflections less through the polarized filter on the camera for any highlighted signal. For the more, the data processing time and the noise reduction are effectively implemented by using the wavelet transform of time-space scale with the considerations on the physical loss and processing time.

• Proceedings of the Korea Multimedia Society Conference
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• 2004.05a
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• pp.179-182
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• 2004

무선통신분야에서 LMS5(Least Mean Square) 알고리즘은 식이 간단하고 계산량이 비교적 적기 때문에 널리 사용되고 있다. 그러나 시간영역에서 처리할 경우 입력신호의 고유치 변동폭이 넓게 분포되어 수렴속도가 저하하는 문제점이 있다. 이를 해결하기 위하여 신호를 FFT(Fast Fourier Trasnform)나 DCT(Discrete Cosine Transform)로 변환하여 신호간의 상관도를 제거함으로써 시간영역에서 LMS알고리즘을 적용할 때 보다 수렴속도를 크게 향강시킬 수 있다. 본 논문에서는 수렴속도 향상을 위해 시간영역의 적응 알고리즘을 직교변환인 고속웨이브렛(wavelet)변환을 이용하여 변환영역에서 수행하며, 짧은 필터계수를 가지는 DWT(Discrete Wavelet Transform)특성에 맞는 Fast running FIR 알고리즘을 이용하여 WTLMS(Wavelet Transform LMS)적응알고리즘을 통신시스템에 적용한다. 적응 알고리즘의 성능향상을 위하여 시간에 따라 적응상수의 크기를 가변시켜 수렴 초기에는 큰 적응상수로 따른 수렴이 가능하도록 하고 점차 적응상수의 크기를 줄여서 misadjustment도 줄이는 방법의 적응 알고리즘을 제안하였다. 제안한 알고리즘을 실제로 적응잡음제거기(adaptive noise canceler)에 적용하여 컴퓨터 시뮬레이션을 하였으며, 각 알고리즘들의 계산량, 수렴속도를 이용하여 각각 비교, 분서하여 그 성능이 우수함을 입증하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04d
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• pp.310-312
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• 2003

관성항법 시스템은 항체의 위치, 속도 및 자세정보를 거의 연속적으로 제공할 수 있는 장점이 있다. 그러나 시간의 경과함에 따라 초기오차가 누적되어 발산하게 되는 단점이 있다. 이로 인하여 실제 적용시에는 매우 고가의 정밀한 자이로와 가속도계가 필요하다. 반면 DGPS는 오차의 누적이나 증가없이 장기간 동안 안정적으로 위치정보를 제공하지만 낮은 데이터 전송률과 도심지역과 칼은 곳에서는 신호의 차단이나 전파방해에 영향을 받는 단점이 있다. 이와 같이 상호보완적인 DGPS와 INS 정보를 통합하여 고 정밀의 속도, 위치 및 자세데이터를 제공할 수 있다. 본 논문은 저가의 IMU의 노이즈와 바이어스를 웨이브렛의 soft thresholding 기법을 이용하여 잡음을 제거하여 성능향상을 시도하였다. 통합알고리즘의 필터는 IS차로 구현하였으며 관측치는 DGPS의 위치정보를 이용하였다.

• Journal of Ocean Engineering and Technology
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• v.28 no.6
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• pp.552-559
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• 2014

In general, the number of underwater transient signals is very limited for research on automatic recognition. Data-dependent feature extraction is one of the most effective methods in this case. Therefore, we suggest WPCC (Wavelet packet ceptsral coefficient) as a feature extraction method. A wavelet packet best tree for each data set is formed using an entropy-based cost function. Then, every terminal node of the best trees is counted to build a common wavelet best tree. It corresponds to flexible and non-uniform filter bank reflecting characteristics for the data set. A GMM (Gaussian mixture model) is used to classify five classes of underwater transient data sets. The error rate of the WPCC is compared using MFCC (Mel-frequency ceptsral coefficients). The error rates of WPCC-db20, db40, and MFCC are 0.4%, 0%, and 0.4%, respectively, when the training data consist of six out of the nine pieces of data in each class. However, WPCC-db20 and db40 show rates of 2.98% and 1.20%, respectively, while MFCC shows a rate of 7.14% when the training data consists of only three pieces. This shows that WPCC is less sensitive to the number of training data pieces than MFCC. Thus, it could be a more appropriate method for underwater transient recognition. These results may be helpful to develop an automatic recognition system for an underwater transient signal.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1155-1166
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• 2016

In this paper, we propose a new embedded video compression scheme which uses three-dimensional rate-distortion optimization based block coder. After the proposed scheme removes temporal redundancy by applying the motion compensated temporal filtering(MCTF) on input video frames, two dimensional discrete wavelet transform is applied on video frames to remove spatial redundancy. The three-dimensional wavelet coefficients generated in this way are sorted according to their expected rate-distortion slope and encoded by using the three-dimensional block partition coding method. The proposed scheme also uses both the effective color video coding method which maintains embedded features, and the efficient bit-rate control method. Experimental results demonstrate that the proposed scheme not only produces embedded bit-streams, but also outperforms existing video compression schemes.

• Journal of Biomedical Engineering Research
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• v.22 no.3
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• pp.249-257
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• 2001

The voluntary contracted EMG signal of spinal cord injured patients is very small because the information from central nervous system is not sufficiently transmitted to $\alpha$ motor neuron or muscle fiber. Therefore the acquisited EMG signal from needle or surface electrodes can not be identified obvious voluntary contraction pattern by muscle movement. In this paper we propose the extraction technique of voluntary muscle contraction and relaxation pattern from EMG signal of spinal cord injured patient whose EMG signal is composed of the linear sum of mo색 unit action potentials with two noise sources, additive noise assumed to be white Gaussian noise and high frequency discharge assumed to be not motor unit action potential but impulsive noise. In order to eliminate impulsive noise and additive noise from voluntary contracted EMG signal, we use the FatBear filter which is a nonarithmetic piecewise constant filter, and multiscale nonlinear wavelet denoising processing, respectively. The proposed technique is applied to the EMG signal acquisited from transverse myelitis patients to extract voluntary muscle contraction pattern.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.5 s.305
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• pp.27-34
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• 2005

Ventricular fibrillation(VF) is generally caused by chaotic behavior of electrical propagation in heart and may result in sudden cardiac death. In this study, we proposed a ventricular fibrillation detection algorithm based on support vector machine classifier, which could offer benefits to reduce the teaming costs as well as good classification performance. Before the extraction of input features, raw ECG signal was applied to preprocessing procedures, as like wavelet transform based bandpass filtering, R peak detection and segment assignment for feature extraction. We selected input features which of some are related to the rhythm information and of others are related to wavelet coefficients that could describe the morphology of ventricular fibrillation well. Parameters for SVM classifier, C and ${\alpha}$, were chosen as 10 and 1 respectively by trial and error experiments. Each average performance for normal sinus rhythm ventricular tachycardia and VF, was 98.39%, 96.92% and 99.88%. And, when the VF detection performance of SVM classifier was compared to that of multi-layer perceptron and fuzzy inference methods, it showed similar or higher values. Consequently, we could find that the proposed input features and SVM classifier would one of the most useful algorithm for VF detection.

• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.149-160
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• 2015

A comparative study was conducted for alternative consecutive procedures of detection of cloud-contaminated pixels and gap-filling and smoothing of time-series data to produce high-quality gapless satellite vegetation index (i.e. Normalized Difference Vegetation Index, NDVI). Performances of five alternative methods for detecting cloud contaminations were tested with ground-observed cloudiness data. The data gap was filled with a simple linear interpolation and then, it was applied two alternative smoothing methods (i.e. Savitzky-Golay and Wavelet transform). Moderate resolution imaging spectroradiometer (MODIS) data were used in this study. Among the alternative cloud detection methods, a criterion of MODIS Band 3 reflectance over 10% showed best accuracy with an agreement rate of 85%, which was followed by criteria of MODIS Quality assessment (82%) and Band 3 reflectance over 20% (81%), respectively. In smoothing process, the Savitzky-Golay filter was better performed to retain original NDVI patterns than the wavelet transform. This study demonstrated an operational framework of gapdetection, filling, and smoothing to produce high-quality satellite vegetation index.