• Title/Summary/Keyword: Data Transform

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Measurement of Vibration Mode Shape By Using Hilbert Transform (Hilbert Transform을 이용한 진동모드 측정)

  • Kang, Min-Sig
    • Proceedings of the KSME Conference
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    • 2001.06b
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    • pp.392-397
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    • 2001
  • This paper concerns on modal analysis of mechanical structures by using a continuous scanning laser Doppler vibrometer. In modal analysis the Hilbert transform based approach is superior to the Fourier transform based approach because of its fine accuracy and its flexible experimental settings. In this paper the Hilbert transform based approach is extended to measure area mode shape data of a structure by simply modifying the scanning pattern ranging the entire surface of the structure. The effectiveness of this proposed method is illustrated along with results of numerical simulation for a rectangular plate.

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Analysis of the Complementary Clipping Transform technique for the PAPR reduction of OFDM system (OFDM PAPR reduction을 위한 Complementary Clipping Transform 성능 분석)

  • Won, Seong-Ho
    • Proceedings of the Korea Electromagnetic Engineering Society Conference
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    • 2005.11a
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    • pp.57-62
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    • 2005
  • In spite of many advantages of OFDM, a major drawback for implementation is a non-linear distortion in the HPA due to a high PAPR problem. In this paper, the Complementary Clipping Transform technique (CCT) for the PAPR reduction of OFDM system is analyzed for the QPSK and QAM mapping data. BER performance and PSD in front of HPA and after HPA are analytically demonstrated.

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AN APPLICATION OF p-ADIC ANALYSIS TO WINDOWED FOURIER TRANSFORM

  • Park, Sook Young;Chung, Phil Ung
    • Korean Journal of Mathematics
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    • v.12 no.2
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    • pp.193-200
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    • 2004
  • We shall introduce the notion of the windowed Fourier transform in $\mathbb{Q}_p$ and show that, for any given function $g{\in}L^2(\mathbb{Q}_p)$ of norm, the windowed Fourier transform of $f$ with respect to $g$ be a function of norms, and moreover be expressible to a summation form. The results obtained in this paper will be usable to the field of research in data compression for signal processing according to the following scheme.

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A Single Index Approach for Subsequence Matching that Supports Normalization Transform in Time-Series Databases (시계열 데이터베이스에서 단일 색인을 사용한 정규화 변환 지원 서브시퀀스 매칭)

  • Moon Yang-Sae;Kim Jin-Ho;Loh Woong-Kee
    • The KIPS Transactions:PartD
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    • v.13D no.4 s.107
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    • pp.513-524
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    • 2006
  • Normalization transform is very useful for finding the overall trend of the time-series data since it enables finding sequences with similar fluctuation patterns. The previous subsequence matching method with normalization transform, however, would incur index overhead both in storage space and in update maintenance since it should build multiple indexes for supporting arbitrary length of query sequences. To solve this problem, we propose a single index approach for the normalization transformed subsequence matching that supports arbitrary length of query sequences. For the single index approach, we first provide the notion of inclusion-normalization transform by generalizing the original definition of normalization transform. The inclusion-normalization transform normalizes a window by using the mean and the standard deviation of a subsequence that includes the window. Next, we formally prove correctness of the proposed method that uses the inclusion-normalization transform for the normalization transformed subsequence matching. We then propose subsequence matching and index building algorithms to implement the proposed method. Experimental results for real stock data show that our method improves performance by up to $2.5{\sim}2.8$ times over the previous method. Our approach has an additional advantage of being generalized to support many sorts of other transforms as well as normalization transform. Therefore, we believe our work will be widely used in many sorts of transform-based subsequence matching methods.

A Study on the Sonar Data Processing by Using a Discrete Wavelet Transform (이산 웨이브릿 변환을 이용한 소나 자료처리에 관한 연구)

  • Kim, Jin-Hoo;Kim, Hyun-Do
    • Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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    • 2003.05a
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    • pp.324-329
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    • 2003
  • Spectral analysis is an important signal processing tool for time series data. The transformation of a time series into the frequency domain is the basis for a significant number of processing algorithms and interpretive methods. Recently developed transforms based on the new mathematical field of wavelet analysis bypass the resolution limitation and offer superior spectral decomposition. The discrete wavelet transform of Sonar data provides spectral localization of noises, hence noises can be filtered out successfully.

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Multi-scale Correlation Analysis between Sea Level Anomaly and Climate Index through Wavelet Approach (웨이블릿 접근을 통한 해수면 높이와 기후 지수간의 다중 스케일 상관 관계 분석)

  • Hwang, Do-Hyun;Jung, Hahn Chul
    • Korean Journal of Remote Sensing
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    • v.38 no.5_1
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    • pp.587-596
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    • 2022
  • Sea levels are rising as a result of climate change, and low-lying areas along the coast are at risk of flooding. Therefore, we tried to investigate the relationship between sea level change and climate indices using satellite altimeter data (Topex/Poseidon, Jason-1/2/3) and southern oscillation index (SOI) and the Pacific decadal oscillation (PDO) data. If time domain data were converted to frequency domain, the original data can be analyzed in terms of the periodic components. Fourier transform and Wavelet transform are representative periodic analysis methods. Fourier transform can provide only the periodic signals, whereas wavelet transform can obtain both the periodic signals and their corresponding time location. The cross-wavelet transformation and the wavelet coherence are ideal for analyzing the common periods, correlation and phase difference for two time domain datasets. Our cross-wavelet transform analysis shows that two climate indices (SOI, PDO) and sea level height was a significant in 1-year period. PDO and sea level height were anti-phase. Also, our wavelet coherence analysis reveals when sea level height and climate indices were correlated in short (less than one year) and long periods, which did not appear in the cross wavelet transform. The two wavelet analyses provide the frequency domains of two different time domain datasets but also characterize the periodic components and relative phase difference. Therefore, our research results demonstrates that the wavelet analyses are useful to analyze the periodic component of climatic data and monitor the various oceanic phenomena that are difficult to find in time series analysis.

The Rank Transform Method in Nonparametric Fuzzy Regression Model

  • Choi, Seung-Hoe;Lee, Myung-Sook
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.3
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    • pp.617-624
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    • 2004
  • In this article the fuzzy number rank and the fuzzy rank transformation method are introduced in order to analyse the non-parametric fuzzy regression model which cannot be described as a specific functional form such as the crisp data and fuzzy data as a independent and dependent variables respectively. The effectiveness of fuzzy rank transformation methods is compared with other methods through the numerical examples.

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Fast Inverse Transform Considering Multiplications (곱셈 연산을 고려한 고속 역변환 방법)

  • Hyeonju Song;Yung-Lyul Lee
    • Journal of Broadcast Engineering
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    • v.28 no.1
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    • pp.100-108
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    • 2023
  • In hybrid block-based video coding, transform coding converts spatial domain residual signals into frequency domain data and concentrates energy in a low frequency band to achieve a high compression efficiency in entropy coding. The state-of-the-art video coding standard, VVC(Versatile Video Coding), uses DCT-2(Discrete Cosine Transform type 2), DST-7(Discrete Sine Transform type 7), and DCT-8(Discrete Cosine Transform type 8) for primary transform. In this paper, considering that DCT-2, DST-7, and DCT-8 are all linear transformations, we propose an inverse transform that reduces the number of multiplications in the inverse transform by using the linearity of the linear transform. The proposed inverse transform method reduced encoding time and decoding time by an average 26%, 15% in AI and 4%, 10% in RA without the increase of bitrate compared to VTM-8.2.

Power System Fault Monitoring System using Wavelelet Transform and GPS for Accurate Time Synchronization (웨이블릿 변환과 GPS 정밀시각동기를 이용한 전력계통 고장점 모니터링 시스템에 관한 연구)

  • Kim, Gi-Taek;Kim, Hyuck-Soo;Choi, Jung-Yong
    • Journal of Industrial Technology
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    • v.21 no.A
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    • pp.105-110
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    • 2001
  • A continuous and reliable electrical energy supply is the objective of any power system operation. A transmission line is the part of the power system where faults are most likely to happen. This paler describes the use of wavelet transform for analyzing power system fault transients in order to determine the fault location. Synchronized sampling was made possible by precise time receivers based on GPS time reference, and the sampled data were analyzed using wavelet transform. This paper describes a fault location monitoring system and fault locating algorithm with GPS, DSP processor, and data acquisition board, and presents some experimental results and error analysis.

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A study on a FPGA based implementation of the 2 dimensional discrete wavelet transform using a fast lifting scheme algorithm for the JPEG2000 image compression (JPEG2000 영상압축을 위한 리프팅 설계 알고리즘을 이용한 2차원 이산 웨이블릿 변환 프로세서의 FPGA 구현에 대한 연구)

  • 송영규;고광철;정제명
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.2315-2318
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    • 2003
  • The Wavelet Transform has been applied in mathematics and computer sciences. Numerous studies have proven its advantages in image processing and data compression, and have made it a basic encoding technique in data compression standards like JPEG2000 and MPEG-4. Software implementations of the Discrete Wavelet Transform (DWT) appears to be the performance bottleneck in real-time systems in terms of performance. And hardware implementations are not flexible. Therefore, FPGA implementations of the DWT has been a topic of recent research. The goal of this thesis is to investigate of FPGA implementations of the DWT Processor for image compression applications. The DWT processor design is based on the Lifting Based Wavelet Transform Scheme, which is a fast implementation of the DWT The design uses various techniques. The DWT Processor was simulated and implemented in a FLEX FPGA platform of Altera

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