• Title/Summary/Keyword: Data Transform

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CUDA 기반 병렬 Haar Transform 고찰

  • Lee, Sang-Il;Park, Neung-Soo
    • Annual Conference of KIPS
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    • 2009.11a
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    • pp.249-250
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    • 2009
  • 음향 신호 이미지 처리, human vision 등의 분야에서 널리 쓰이는 wavelet transform의 가장 간단한 형태인 one-dimension haar wavelet transform을 CUDA로 구현하고 hardware 특성을 살린 optimizing을 함으로써 Data-parallelism의 성능과 CUDA memory architecture의 상관 관계를 살펴본다.

Control Limits of Time Series Data using Hilbert-Huang Transform : Dealing with Nested Periods (힐버트-황 변환을 이용한 시계열 데이터 관리한계 : 중첩주기의 사례)

  • Suh, Jung-Yul;Lee, Sae Jae
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.37 no.4
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    • pp.35-41
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    • 2014
  • Real-life time series characteristic data has significant amount of non-stationary components, especially periodic components in nature. Extracting such components has required many ad-hoc techniques with external parameters set by users in a case-by-case manner. In this study, we used Empirical Mode Decomposition Method from Hilbert-Huang Transform to extract them in a systematic manner with least number of ad-hoc parameters set by users. After the periodic components are removed, the remaining time-series data can be analyzed with traditional methods such as ARIMA model. Then we suggest a different way of setting control chart limits for characteristic data with periodic components in addition to ARIMA components.

Strong Uncorrelated Transform Applied to Spatially Distant Channel EEG Data

  • Kim, Youngjoo;Park, Cheolsoo
    • IEIE Transactions on Smart Processing and Computing
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    • v.4 no.2
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    • pp.97-102
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    • 2015
  • In this paper, an extension of the standard common spatial pattern (CSP) algorithm using the strong uncorrelated transform (SUT) is used in order to extract the features for an accurate classification of the left- and right-hand motor imagery tasks. The algorithm is designed to analyze the complex data, which can preserve the additional information of the relationship between the two electroencephalogram (EEG) data from distant channels. This is based on the fact that distant regions of the brain are spatially distributed spatially and related, as in a network. The real-world left- and right-hand motor imagery EEG data was acquired through the Physionet database and the support vector machine (SVM) was used as a classifier to test the proposed method. The results showed that extracting the features of the pair-wise channel data using the strong uncorrelated transform complex common spatial pattern (SUTCCSP) provides a higher classification rate compared to the standard CSP algorithm.

A Study on the Removal of Impulse Noiseusing Wavelet Transform Pair and Adaptive-Length Median filter (웨이브렛 변환쌍과 적응-길이 메디안 필터를 이용한 임펄스 노이즈 제거에 관한 연구)

  • 배상범;김남호
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.7
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    • pp.1575-1581
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    • 2003
  • As a society has progressed rapidly toward a highly advanced digital information age, a multimedia communication service for acquisition, transmission and storage of image data as well as voice has being commercialized externally and internally. However, in the process of digitalization or transmission of data, noise is generated by several causes, and researches for eliminating those noises have been continued until now. There were the existing FFT(fast fourier transform) and STFT(short time fourier transform) for removing noise but it's impossible to know information about time and time-frequency localization capabilities has conflictive relationship. Therefore, for overcoming these limits, wavelet transform which is presented as a new technique of signal processing field is being applied in many fields recently. Because it has time-frequency localization capabilities it's Possible for multiresolution analysis as well as easy to analyze various signal. And when two wavelet base were designed to form Hilbert transform pair, wavelet pair provide superior performance than the existing DWT(discrete wavelet transform) in data characteristic detection. Therefore in this parer, we removed impulse noise by using adaptive-length median filter and two dyadic wavelet base which is designed by truncated coefficient vector.

Hybrid Color and Grayscale Images Encryption Scheme Based on Quaternion Hartley Transform and Logistic Map in Gyrator Domain

  • Li, Jianzhong
    • Journal of the Optical Society of Korea
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    • v.20 no.1
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    • pp.42-54
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    • 2016
  • A hybrid color and grayscale images encryption scheme based on the quaternion Hartley transform (QHT), the two-dimensional (2D) logistic map, the double random phase encoding (DRPE) in gyrator transform (GT) domain and the three-step phase-shifting interferometry (PSI) is presented. First, we propose a new color image processing tool termed as the quaternion Hartley transform, and we develop an efficient method to calculate the QHT of a quaternion matrix. In the presented encryption scheme, the original color and grayscale images are represented by quaternion algebra and processed holistically in a vector manner using QHT. To enhance the security level, a 2D logistic map-based scrambling technique is designed to permute the complex amplitude, which is formed by the components of the QHT-transformed original images. Subsequently, the scrambled data is encoded by the GT-based DRPE system. For the convenience of storage and transmission, the resulting encrypted signal is recorded as the real-valued interferograms using three-step PSI. The parameters of the scrambling method, the GT orders and the two random phase masks form the keys for decryption of the secret images. Simulation results demonstrate that the proposed scheme has high security level and certain robustness against data loss, noise disturbance and some attacks such as chosen plaintext attack.

Fuzzy Data Fitting With Genetic Algorithm (유전자 알고리즘을 이용한 Fuzzy Data Fitting)

  • 김성용;한준희
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10c
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    • pp.479-481
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    • 1998
  • Noise가 있는 data에서 shape나 parameter를 찾았을 때 일반적으로 Hough transform이나 regression을 적용한다. Hough transform은 parameter space의 차수가 커지면 memory 문제가 존재하며, regression 모델은 한 개의 변수를 다른 변수의 함수로 가정하여 error를 최소화하여 데이터중 1 set의 parameter만 존재한다는 가정을 하여야 하는 문제점이 있다. 본 논문에서는 이러한 두 방법의 단점들을 보완하며, Fuzzy개념을 도입한 data fitting 방법을 제안하였다. 이 문제는 genetic algorithm을 도입하여 data를 Fuzzy membership을 갖는 것으로 가정한 최적화 문제로 해결하였다. 직선과 평면에 대한 실험 결과를 보인다.

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Vibration Data Denoising and Performance Comparison Using Denoising Auto Encoder Method (Denoising Auto Encoder 기법을 활용한 진동 데이터 전처리 및 성능비교)

  • Jang, Jun-gyo;Noh, Chun-myoung;Kim, Sung-soo;Lee, Soon-sup;Lee, Jae-chul
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.27 no.7
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    • pp.1088-1097
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    • 2021
  • Vibration data of mechanical equipment inevitably have noise. This noise adversely af ects the maintenance of mechanical equipment. Accordingly, the performance of a learning model depends on how effectively the noise of the data is removed. In this study, the noise of the data was removed using the Denoising Auto Encoder (DAE) technique which does not include the characteristic extraction process in preprocessing time series data. In addition, the performance was compared with that of the Wavelet Transform, which is widely used for machine signal processing. The performance comparison was conducted by calculating the failure detection rate. For a more accurate comparison, a classification performance evaluation criterion, the F-1 Score, was calculated. Failure data were detected using the One-Class SVM technique. The performance comparison, revealed that the DAE technique performed better than the Wavelet Transform technique in terms of failure diagnosis and error rate.

A Pipelined Hadamard Transform Processor (파이프라인 방식에 의한 아다마르 변환 프로세서)

  • 황영수;윤대희;차일환
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.26 no.10
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    • pp.1617-1623
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    • 1989
  • The introduction of the fast Fourier transform(FFT),an efficient computational algorithm for the discrete Fourier transform(DFT) by Cooley and Tukey(1965), has brought to the limelight various other discrete transforms. Some of the analog functions from which these transforms have been derived date back to the early 1920's, for example, Walsh functions (Walsh, 1923) and Hadamard Transform(Enomoto et al, 1965). Fast algorithms developed for the forward transform are equally applicable, exept for minor changes, to the inverse transform. In this paper, we present a simple pipelined Hadamard matrix(HM) which is used to develop a fast algorithm for the Hadamard Processor (HP). The Fast Hadamard Transform(FHT) can be derived using matrix partitioning techniques. The HP system is incorporated through a modular design which permits tailoring to meet a wide range of video data link applications. Emphasis has been placed on a low cost, a low power design suitable for airbone system and video codec.

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Estimated spectrum of a 6MV X-ray (Laplace transform 방법에 의한 x-ray의 에너지 스펙트럼 추정)

  • Yoo, Myung-Jin
    • Progress in Medical Physics
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    • v.4 no.2
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    • pp.37-47
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    • 1993
  • The quality of radiation for a high energy x-ray beam can be specified by its attenuation curve in a selected material. The inverse Laplace transform of the attenuation curve can be used as an approximate indication of the energy spectrum of the beam. We have made a comparative investigation of the estimated spectrum obtained by the Laplace transform analysis of the transmitted exposure data measured in an absorption study of a 6MV x-ray beam. Two of existing transform pair models have been investicated and discussed.

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Multiple Description Coding using Whitening Transform (Whitening Transform을 이용한 Multiple Description Coding)

  • 최광표;이근영
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.41-44
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    • 2002
  • In the communications systems with diversity, we are commonly faced on needing of new source coding technique, error resilient coding. The error resilient coding addresses the coding algorithm that has the robustness to unreliability of communications channel. In recent years, many error resilient coding techniques were proposed such as data partitioning, resynchronization, error detection, concealment, reference picture selection and multiple description coding (MDC). In this paper, we proposed an MDC using whitening transform. The conventional MDC using correlating transform is need additional information to decode the image. But, if an image is transformed using the whitening transform, the additional information is not necessary to transform because the coefficients of whitening transform have uni-variance statistics.

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