• Smart Structures and Systems
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• 제30권3호
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• pp.263-271
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• 2022

In this paper we present an overview of damage diagnosis algorithms that have been developed over the past two decades using vibration signals obtained from structures. Then, the paper focuses primarily on algorithms that can be used following an extreme event such as a large earthquake to identify structural damage for responding in a timely manner. The algorithms presented in the paper use measurements obtained from accelerometers and gyroscope to identify the occurrence of damage and classify the damage. Example algorithms are presented include those based on autoregressive moving average (ARMA), wavelet energies from wavelet transform and rotation models. The algorithms are illustrated through application of data from test structures such as the ASCE Benchmark structure and laboratory tests of scaled bridge columns and steel frames. The paper concludes by identifying needs for research and development in order for such algorithms to become viable in practice.

• Structural Engineering and Mechanics
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• 제64권6권
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• pp.803-817
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• 2017

Structural health monitoring has increasingly been a focus within the civil engineering research community over the last few decades. With increasing application of sensor networks in large structures and infrastructure systems, effective use and development of robust algorithms to analyze large volumes of data and to extract the desired features has become a challenging problem. In this paper, we grasp some precautions and key points of the signal processing approach, wavelet, establish a relative reliable framework, and analyze three problems that require attention when applying wavelet based damage detection approach. The cases studies how to use optimal scales for extracting mode shapes and modal curvatures in a reinforced concrete beam and how to effectively identify damages using maximum curves of wavelet coefficient differences. Moreover, how to make a recognition based on the wavelet multi-resolution analysis, wavelet packet energy, and fuzzy sets is a meaningful topic that has been addressed in this work. The relative systematic work that compasses algorithms, structures and evaluation paves a way to a framework regarding effective structural health monitoring, orientation, decision and action.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 추계종합학술대회 논문집
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• pp.851-854
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• 1998

Recently efficient image coding algorithms using zerotree have been proposed. In these methods, the locations of nonzero wavelet coefficients are encoded with a tree structure, called zerotree, which can exploit the self-similarity of the wavelet pyramid decomposition across different scales. These are very effective, especially in low bit rate image coding. In this paper, two zerotree image coding algorithms, EZW and SPIHT, are briefly introduced, and a new zerotree searching scheme is proposed to emphasize the significance of a wavelet coefficient by its orientations as well as its scale.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권9호
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• pp.663-669
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• 2004

The mobile tole-cardiology system is the new research area that support an ubiquitous health care based on mobile telecommunication networks. Although there are many researches presenting the modeling concepts of a GSM-based mobile telemedical system, practical application needs to be considered both compression performance and error corruption in the mobile environment. This paper evaluates three wavelet ECG compression algorithms over CDMA networks. The three selected methods are Rajoub using EPE thresholding, Embedded Zerotree Wavelet(EZW) and Wavelet transform Higher Order Statistics Coding(WHOSC) with linear prediction. All methodologies protected more significant information using Forward Error Correction coding and measured not only compression performance in noise-free but also error robustness and delay profile in CDMA environment. In addition, from the field test we analyzed the PRD for movement speed and the features of CDMA 1X. The test results show that Rajoub has low robustness over high error attack and EZW contributes to more efficient exploitation in variable bandwidth and high error. WHOSC has high robustness in overall BER but loses performance about particular abnormal ECG.

• 방송공학회논문지
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• 제17권2호
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• pp.344-353
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• 2012

본 논문에서는 이산 웨이블릿 변환(Discrete Wavelet Transform: DWT)을 이용한 새로운 초고해상도 기법을 제안한다. 기존의 단일 영상에 적용되는 초고해상도 기법들의 경우 영상에서의 고주파 대역을 찾기 위하여 확률 기반의 방법들을 사용하였다. 그로 인한 연산의 복잡도 증가는 처리시간 증가라는 문제점을 발생시켰다. 제안된 기법에서는 고주파 대역을 찾기 위한 방법으로 DWT를 이용한다. DWT 수행 시 수반되는 다운 샘플링 과정을 수행하지 않음으로써 입력 받은 영상과 동일한 크기의 고주파 부대역(sub-band)들을 생성하고, 이 부대역들과 입력 받은 영상을 조합하여 이산 웨이블릿 역변환(Inverse Discrete Wavelet Transform: Inverse DWT)을 수행함으로써 고해상도의 영상을 획득한다. 제안하는 기법에서 사용한 실험영상은 원본영상($512{\times}512$)을 다운 샘플링하여 획득한 실험영상($256{\times}256$)을 사용한다. 실험을 통하여 제안된 기법이 기존의 보간법에 비해 향상된 효율을 보이며, 확률 기반의 기법들에 비해 처리시간이 줄어드는 것을 확인하였다.

• 대한수학회지
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• 제33권4호
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• pp.955-982
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• 1996

In surface compression applications, one of the main issues is how to efficiently store and calculate the computer representation of certain surfaces. This leads us to consider a nonlinear approximation by box splines with free knots since, for instance, the nonlinear method based on wavelet decomposition gives efficient compression and recovery algorithms for such surfaces (cf. [12]).

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2000년도 하계종합학술대회논문집
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• pp.45-48
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• 2000

In this paper algorithms of frequency hopping sequences generation such as Lempel-Greenberger, optimum Lempel-Greenberger and Kumar sequences for spread spectrum communications are described. Using the scalogram based on wavelet transform, time-frequency characteristics of frequency hopped signals corresponding to the considered hopping sequences are analyzed.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.224-227
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• 2004

From 1980's, the DWT(Discrete Wavelet Transform) is applied to the data/image processing. Many people use the DWT in remote sensing for diversity purposes and they are satisfied with the wavelet theory. Though the algorithm for wavelet is very diverse, many people use the standard wavelet such as Daubechies D4 wavelet and biorthogonal 9/7 wavelet. We will overview the wavelet theory for discrete form which can be applied to the image processing. First, we will introduce the basic DWT algorithm and review the wavelet algorithm: EZW (Embedded Zerotree Wavelet), SPIHT(Set Partitioning in Hierarchical Trees), Lifting scheme, Curvelet, etc. Finally, we will suggest the properties of wavelet algorithm; and wavelet filter for each image processing in remote sensing.

• 대한의용생체공학회:의공학회지
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• 제15권3호
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• pp.305-316
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• 1994

All physical data in the real world are nonstationary signals that have the time varying statistical characteristics. Although few algorithms suitable to process the nonstationary signals have ever been suggested, these are treated the nonstationary signals under the assumption that the nonstationary signal is a piece-wise stationary signal. Recently, statistical analysis algorithms for the nonstationary signal have concentrated so much interest. In this paper, nonstationary EMG signals are mapped onto the orthogonal wavelet transform domain so that the eigenvalue spread of its autocorrelation matrix could be more smaller than that in the time domain. Then the model in the wavelet transform domain and an algorithm to estimate the model parameters are suggested. Also, an test signal generated by a white gaussian noise and the EMG signal are identified, and the algorithm performance is considered in the sense of the mean square error and the evaluation parameters.

• Journal of Information Processing Systems
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• 제13권5호
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• pp.1331-1344
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• 2017

In this paper, data hiding algorithm using Discrete Wavelet Transform (DWT) and Arnold Transform is proposed. The secret data is scrambled using Arnold Transform to make it secure. Wavelet subbands of a cover image are obtained using DWT. The scrambled secret data is embedded into significant wavelet coefficients of subbands of a cover image. The proposed algorithm is robust to a variety of attacks like JPEG and JPEG2000 compression, image cropping and median filtering. Experimental results show that the PSNR of the composite image is 1.05 dB higher than the PSNR of existing algorithms and capacity is 25% higher than the capacity of existing algorithms.