• Title, Summary, Keyword: Discrete stationary wavelet transform

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A Comparative Study on Classification Methods of Sleep Stages by Using EEG

  • Kim, Jinwoo
    • Journal of Korea Multimedia Society
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    • v.17 no.2
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    • pp.113-123
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    • 2014
  • Electrophysiological recordings are considered a reliable method of assessing a person's alertness. Sleep medicine is asked to offer objective methods to measure daytime alertness, tiredness and sleepiness. As EEG signals are non-stationary, the conventional method of frequency analysis is not highly successful in recognition of alertness level. In this paper, EEG signals have been analyzed using wavelet transform as well as discrete wavelet transform and classification using statistical classifiers such as euclidean and mahalanobis distance classifiers and a promising method SVM (Support Vector Machine). As a result of simulation, the average values of accuracies for the Linear Discriminant Analysis (LDA)-Quadratic, k-Nearest Neighbors (k-NN)-Euclidean, and Linear SVM were 48%, 34.2%, and 86%, respectively. The experimental results show that SVM classification method offer the better performance for reliable classification of the EEG signal in comparison with the other classification methods.

Spike Rejection Method for Improving Altitude Control Performance of Quadrotor UAV Using Ultrasonic Rangefinder (초음파 거리계를 이용하는 쿼드로터 무인항공기의 고도 제어 성능 향상을 위한 스파이크 제거 기법)

  • Kim, Sung-Hoon;Choi, Kyeung-Sik;Hong, Gyo-Young
    • The Journal of Advanced Navigation Technology
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    • v.20 no.3
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    • pp.196-202
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    • 2016
  • In this paper, a stationary wavelet transform method is proposed for improving the altitude control performance of quadrotor UAV using an ultrasonic rangefinder. A ground tests are conducted using an ultrasonic rangefinder that is much used for vertical takeoff and landing. An ultrasonic rangefinder suffers from signal's spike due to specular reflectance and acoustic noise. The occurred spikes in short time span need to be analyzed at both sides time and frequency domain. It was known that stationary wavelet transform is the transferring solution to the problem occurred by down sampling from DWT also more efficient to remove noise than DWT. The analyzed spikes of the ultrasonic rangefinder using a stationary wavelet transform and experimental results show that it can effectively remove the spikes of the ultrasonic rangefinder.

Power Quality Data Compression using Wavelet Transform (웨이브렛 변환을 이용한 전력품질 데이터 압축에 관한 연구)

  • Chung Young-Sik
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.54 no.12
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    • pp.561-566
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    • 2005
  • This paper introduces a compression technique for power qualify disturbance signal via discrete wavelet transform(DWT). The proposed approach is based on a previous estimation of the stationary component of power quality disturbance signal, so that it could be subtracted from the original signal in order to reduce a dynamic range of signal and generate transient events signal, which is subsequently applied to the compression technique. The compression techniques is performed through the difference signal decomposition, thresholding of wavelet coefficients, and signal reconstruction. It presents the relation between compression efficiency and threshold. It shouts that the wavelet transform leads to a power quality data compression approach with high compression efficiency, small compression error and good de-nosing effect.

A Study on the Wavelet Transform of Acoustic Emission Signals Generated from Fusion-Welded Butt Joints in Steel during Tensile Test and its Applications (맞대기 용접 이음재 인장시험에서 발생한 음향방출 신호의 웨이블릿 변환과 응용)

  • Rhee, Zhang-Kyu
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.16 no.1
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    • pp.26-32
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    • 2007
  • This study was carried out fusion-welded butt joints in SWS 490A high strength steel subjected to tensile test that load-deflection curve. The windowed or short-time Fourier transform(WFT or STFT) makes possible for the analysis of non-stationary or transient signals into a joint time-frequency domain and the wavelet transform(WT) is used to decompose the acoustic emission(AE) signal into various discrete series of sequences over different frequency bands. In this paper, for acoustic emission signal analysis to use a continuous wavelet transform, in which the Gabor wavelet base on a Gaussian window function is applied to the time-frequency domain. A wavelet transform is demonstrated and the plots are very powerful in the recognition of the acoustic emission features. As a result, the technique of acoustic emission is ideally suited to study variables which control time and stress dependent fracture or damage process in metallic materials.

Improvement of EEG-Based Drowsiness Detection System Using Discrete Wavelet Transform (DWT를 적용한 EEG 기반 졸음 감지 시스템의 성능 향상)

  • Han, Hyungseob;Song, Kyoung-Young
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.9
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    • pp.1731-1733
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    • 2015
  • Since electroencephalogram(EEG) has non-linear and non-stationary properties, it is effective to analyze the characteristic of EEG with time-frequency method rather than spectrum method. In this letter, we propose the modified drowsiness detection system using discrete wavelet transform combined with errors-in-variables and multilayer perceptron methods. For the comparison of the proposed scheme with the previous one, the state 'others' is added to the previous states of drivers: 'alertness,' 'transition,' and 'drowsiness.' From the computer simulation using machine learning, we confirm that the proposed scheme outperforms the previous one for some conditions.

웨이브렛 필터를 이용한 위성영상에서의 잡음 제거

  • Ryu, Hui-Yeong;Lee, Gi-Won;Gwon, Byeong-Du
    • 한국지구과학회:학술대회논문집
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    • pp.400-407
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    • 2005
  • 웨이브렛 변환(Wavelet Transform)은 시간영역과 주파수영역에서 동시에 분석이 가능하고 불연속적인 자료를 분석하는데 유리하기 때문에 그동안 영상을 처리하고 분석하는데 널리 이용되어 왔다. Discrete Wavelet Transform(DWT)는 주어진 영상에서 특성 정보는 유지하면서 다른 여러 종류의 계수로 분해 할 수 있게 해주기 때문에, 계수에 임계치를 적용해 고주파 성분을 제거하면 잡음을 줄일 수 있다. Stationary Wavelet Transform(SWT)는 DWT에서 다운샘플링에 의해 발생하는 문제점을 해결하기 위한 변환방법으로 잡음제거에 DWT보다 효과적이라고 알려져 있다. 이 연구에서는 DWT와 SWT에 의한 필터링을 광학영상과 레이더 영상에 적용하여 보고, 기존의 필터링 기법과 그 결과를 비교하였다. 그 결과 SWT에 의한 방법이 경계성분은 보존하면서 잡음을 가장 효과적으로 줄일 수 있었다.

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Secured Authentication through Integration of Gait and Footprint for Human Identification

  • Murukesh, C.;Thanushkodi, K.;Padmanabhan, Preethi;Feroze, Naina Mohamed D.
    • Journal of Electrical Engineering and Technology
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    • v.9 no.6
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    • pp.2118-2125
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    • 2014
  • Gait Recognition is a new technique to identify the people by the way they walk. Human gait is a spatio-temporal phenomenon that typifies the motion characteristics of an individual. The proposed method makes a simple but efficient attempt to gait recognition. For each video file, spatial silhouettes of a walker are extracted by an improved background subtraction procedure using Gaussian Mixture Model (GMM). Here GMM is used as a parametric probability density function represented as a weighted sum of Gaussian component densities. Then, the relevant features are extracted from the silhouette tracked from the given video file using the Principal Component Analysis (PCA) method. The Fisher Linear Discriminant Analysis (FLDA) classifier is used in the classification of dimensional reduced image derived by the PCA method for gait recognition. Although gait images can be easily acquired, the gait recognition is affected by clothes, shoes, carrying status and specific physical condition of an individual. To overcome this problem, it is combined with footprint as a multimodal biometric system. The minutiae is extracted from the footprint and then fused with silhouette image using the Discrete Stationary Wavelet Transform (DSWT). The experimental result shows that the efficiency of proposed fusion algorithm works well and attains better result while comparing with other fusion schemes.

Fault Detection of Reciprocating Compressor for Small-Type Refrigerators Using ART-Kohonen Networks and Wavelet Analysis

  • Yang, Bo-Suk;Lee, Soo-Jong;Han, Tian
    • Journal of Mechanical Science and Technology
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    • v.20 no.12
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    • pp.2013-2024
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    • 2006
  • This paper proposes a condition classification system using wavelet transform, feature evaluation and artificial neural networks to detect faulty products on the production line of reciprocating compressors for refrigerators. The stationary features of vibration signals are extracted from statistical cumulants of the discrete wavelet coefficients and root mean square values of band-pass frequencies. The neural networks are trained by the sample data, including healthy or faulty compressors. Based on training, the proposed system can be used on the automatic mass production line to classify product quality instead of people inspection. The validity of this system is demonstrated by the on-site test at LG Electronics, Inc. for reciprocating compressors. According to different products, this system after some modification may be useful to increase productivity in different types of production lines.

Content Based Dynamic Texture Analysis and Synthesis Based on SPIHT with GPU

  • Ghadekar, Premanand P.;Chopade, Nilkanth B.
    • Journal of Information Processing Systems
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    • v.12 no.1
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    • pp.46-56
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    • 2016
  • Dynamic textures are videos that exhibit a stationary property with respect to time (i.e., they have patterns that repeat themselves over a large number of frames). These patterns can easily be tracked by a linear dynamic system. In this paper, a model that identifies the underlying linear dynamic system using wavelet coefficients, rather than a raw sequence, is proposed. Content based threshold filtering based on Set Partitioning in a Hierarchical Tree (SPIHT) helps to get another representation of the same frames that only have low frequency components. The main idea of this paper is to apply SPIHT based threshold filtering on different bands of wavelet transform so as to have more significant information in fewer parameters for singular value decomposition (SVD). In this case, more flexibility is given for the component selection, as SVD is independently applied to the different bands of frames of a dynamic texture. To minimize the time complexity, the proposed model is implemented on a graphics processing unit (GPU). Test results show that the proposed dynamic system, along with a discrete wavelet and SPIHT, achieve a highly compact model with better visual quality, than the available LDS, Fourier descriptor model, and higher-order SVD (HOSVD).

Abnormal Detection of CTLS Aircraft Wing Structure using SWT (SWT를 이용한 CTLS항공기 날개 구조물 이상탐지)

  • Shin, Hyun-Sung;Hong, Gyo-Young
    • The Journal of Advanced Navigation Technology
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    • v.22 no.5
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    • pp.359-366
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    • 2018
  • In this paper, the noise is removed by using CTLS aircraft installed FBG sensor inside the aircraft wing. We suggest a normal wavelet transform scheme with motion - invariant characteristics for noise reduction. In the case of installing FBG sensors inside the composite material as in CTLS, large and small empty spaces and parts or sections are generated between the adhesive layers, and a signal splitting problem occurs. FBG sensor is not affected by noise. but eletromagnetic, light source, light detector and signal processing device are influeced by noise because these are eletronic components what affected by eletromagnetic wave. because of this, errors are occured. Experimental results show that the noise can be removed using normal wavelet transform and more accurate data detection is possible.