• 융합신호처리학회논문지
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• 제13권1호
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• pp.19-25
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• 2012

An adaptive system is a well-known method for removing noise from noise-corrupted speech. In this paper, we perform a least mean square (LMS) based on wavelet adaptive algorithm. It establishes the faster convergence rate of as compared to time domain because of eigenvalue distribution width. And this paper provides the basic tool required for the FIR algorithm whose algorithm reduces the arithmetic complexity. We consider a new fast short-length running FIR structure in discrete wavelet adaptive algorithm. We compare FIR algorithm and short-length fast running FIR algorithm (SFIR) to the proposed fast short-length running FIR algorithm(FSFIR) for arithmetic complexities.

• 융합신호처리학회논문지
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• 제14권1호
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• pp.13-20
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• 2013

A combined DWT and DCT based watermarking technique of low frequency watermarking with weighted correction is proposed. The DWT has excellent spatial localization, frequency spread and multi-resolution characteristics, which are similar to the theoretical models of the human visual system (HVS). The DCT based watermarking techniques offer compression while DWT based watermarking techniques offer scalability. These desirable properties are used in this combined watermarking technique. In the proposed method watermark bits are embedded in the low frequency band of each DCT block of selected DWT sub-band. The weighted correction is also used to improve the imperceptibility. The extracting procedure reverses the embedding operations without the reference of the original image. Compared with the similar approach by DCT based approach and DWT based approach, the experimental results show that the proposed algorithm apparently preserves superiori mage quality and robustness under various attacks such as JPEG compression, cropping, sharping, contrast adjustments and so on.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.274-274
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• 2000

In the future, the convenient speech command system will become an widely-using interface in automation systems. But the previous research in speech recognition didn't give satisfactory recognition results for the practical realization in the noise environment. The purpose of this research is the development of a practical system, which reliably recognizes the speech command of the registered users, by complementing an existing research which used the image information with the speech signal. For the lip-reading feature extraction from a image, we used the DWT(Discrete Wavelet Transform), which reduces the size and gives useful characteristics of the original image. And to enhance the robustness to the environmental changes of speakers, we acquired the speech signal by stereo method. We designed an economic stand-alone system, which adopted a Bt829 and an AD1819B with a TMS320C31 DSP based add-on board.

• 한국항해항만학회지
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• 제28권2호
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• pp.135-140
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• 2004

A purpose of developing a sound source tracking system in this paper is to reduce the noise efficiently from the received signal by microphone array and measure the signal's time delay between the microphones. I have applied the wavelet analysis algorithm to the system and calculated the sound source's relative position For the performance evaluation, I have compared with the results of utilizing the digital filtering methods based on the FIR LPF using Kaiser window function and the inverse Chebyshev IIR LPF. As a result, I have confirmed the fact that 'time-scale' filter using inverse discrete wavelet transform was suitable for this system.

• 대한전자공학회논문지
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• 제17권1호
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• pp.10-13
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• 1980

위상흔들림이 있는 펀스신호의 전력 스펙트럼을 구하였다. 여기서 pulse sequence는 통계적으로 independent stationary이며 위상흔들림은 stationary Gaussian의 확률특성을 갖는 것으로 가정되었다. Unipolar pulse 신호에 있어서, 위상흔들림이 증가할 때에 전력 스펙트럼의 discrete 부분은 감소하지만 continuous 부분은 증가하는 것으로 나타났다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 제13회 신호처리 합동 학술대회 논문집
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• pp.605-608
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• 2000

This paper introduces a new structure for the undecimated discrete wavelet transform (UDWT). This structure combines the stationary wavelet transform with a lifting scheme and its design is based on a polyphase structure .where the downsampling and split stage are removed. The suggested structure inherits the simplicity of the lifting scheme, such that the inverse transform is easily implemented. The performanace of the proposed undecimated lifting is verified on a signal denoising application.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 A
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• pp.288-290
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• 1999

In view of the importance of DFT(Discrete Fourier Transform) in spectrum analysis, its computation efficiency is a topic. This paper presents calculation time to extract the power frequency at a fault signal using DFT. Furthermore, it is tested a relaying algorithm based on modified DFT and its application to Micro-controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.176-176
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• 2000

Generally, discrete-time processing is applied to the uniformly-sampled signals. But, radars emit pulse trains with irregular time instances. In this paper, we formulate the radar pulse train as a stochastic discrete-time dynamic linear model. The estimation task can be done via linear signal processing using Kalman Filter and some considerations. As a result, we can estimate the pulse repetition interval of a pulse train and predict the time instances of the next pulses to be received.

• 전기의세계
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• 제20권4호
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• pp.17-22
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• 1971

This paper deals with the analytic structure of feedback controller for linear time invariant discrete systems. On the way of developing the deadbeat controller, some necessary conditions for control policy have been derived. In the case of time delay, it was proved that the q periods delay in the control causes q periods delay in the point at which deadbeat response occurs. Theorems and conclusions are illustrated with some simple nontrivial numerical examples and signal state tracking application problems.

• 동력기계공학회지
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• 제14권2호
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• pp.40-47
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• 2010

This paper proposes a fault detection system to detect the strip rupture in six-high stand Cold Rolling Mills based on transient current signal of an electrical motor. For this work, signal smoothing technique is used to highlight precise feature between normal and fault condition. Subtracting the smoothed signal from the original signal gives the residuals that contains the information related to the normal or faulty condition. Using residual signal, discrete wavelet transform is performed and acquire the signal presenting fault feature well. Also, feature extraction and classification are executed by using PCA, KPCA and SVM. The actual data is acquired from POSCO for validating the proposed method.