• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 D
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• pp.2086-2088
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• 2002

This paper deals with an algebraic approach for unknown inputs observer by using Haar functions. In the algebraic UIO(unknown input observer) design procedure, coordinate transformation method is adopted to derive the reduced order dynamic system which is decoupled unknown inputs and Haar function and its integral operational matrix is applied to avoid additional differentiation of system outputs.

• East Asian mathematical journal
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• 제31권5호
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• pp.635-652
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• 2015

It is shown that for a general Haar shift operator, and a weight in the $A_2$ weight class, we establish the weighted norm estimate which linearly depends on $A_2$-characteristic $[w]_{A_2}$. Although the result is now well known, we introduce the new method, which is called the iterated Bellman function method, to provide the estimate.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 D
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• pp.2200-2202
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• 2003

In this paper, differentiation operational matrix for Haar function is derived. Proposed method only using a matrix calculation of Haar discrete matrix and block-pulse function's integration operational matrix. It would be possible to use to design an a1gebraic estimator for fault detection or unknown input observer effectively.

• International Journal of Control, Automation, and Systems
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• 제4권6호
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• pp.714-724
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• 2006

In this note a method of designing optimal vibration control based on Haar functions to control of bounce and pitch vibrations in engine-body vibration structure is presented. Utilizing properties of Haar functions, a computational method to find optimal vibration control for the engine-body system is developed. It is shown that the optimal state trajectories and optimal vibration control are calculated approximately by solving only algebraic equations instead of solving the Riccati differential equation. Simulation results are included to demonstrate the validity and applicability of the technique.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권6호
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• pp.228-234
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• 2002

This paper proposes a real-time application of rationalized Haar transform which is based on the local rationalized Haar transform, local operational matrix and local delay operational matrix. This approach let a general sampling time be used by introducing a scaling factor. In the existing method of orthogonal functions, a major disadvantage is that process signals need to be recorded prior to obtaining their expansions. This paper proposes a novel method of rationalized Haar transform to overcome this shortcoming. And the proposed method is suitable for the analysis of linear systems. The proposed method is expected to the applicable to the adaptive control which demanded to the real-time applications.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 D
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• pp.2129-2131
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• 2002

This paper proposes a real-time application of rationalized Haar transform which is based on the rationalized Haar transform, operational matrix and rationalized Haar function's differential operation. In the existing method of orthogonal functions, a major disadvantage is that process signals need to be recorded prior to obtaining their expansions. This paper proposes a novel method of rationalized Haar transform to overcome this shortcoming. And the proposed method apply to the robust MRAC systems.

• 대한원격탐사학회지
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• 제24권1호
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• pp.57-64
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• 2008

In the previous study, the Haar wavelet was used as the sole basis function for the 3D discrete wavelet transform because the number of bands is too small to decompose a remotely sensed image in band direction with other basis functions. However, it is possible to use other basis functions for wavelet decomposition in horizontal and vertical directions because wavelet decomposition is independently performed in each direction. This study aims to classify a high spatial resolution image with the six types of basis function including the Haar function and to compare those results. The other wavelets are more helpful to classify high resolution imagery than the Haar wavelet. In overall accuracy, the Coif4 wavelet has the best result. The improvement of classification accuracy is different depending on the type of class and the type of wavelet. Using the basis functions with long length could be effective for improving accuracy in classification, especially for the classes of small area. This study is expected to be used as fundamental information for selecting optimal basis function according to the data properties in the 3D DWT based image classification.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 B
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• pp.485-487
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• 1999

We propose the algorithm with which one can solve the problem of the two-level hierarchical optimal control of nonlinear systems by repeatedly updating the state vectors using the haar function and Picard's iteration methods. Using the simple operation of the coefficient vectors from the fast haar transformation in the upper level and applying that vectors to Picard iteration methods in the independently lower level allow us to obtain the another method except the inversion matrix operation of the high dimention and the kronecker product in the optimal control algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2355-2358
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• 2000

This paper presents signal analyzer design, realization of system parameter estimation, analysis and system parameter estimation of distributed parameter systems using orthogonal function like Walsh function, block pulse function and Haar function.

• 한국임상보건과학회지
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• 제4권4호
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• pp.756-761
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• 2016

Purpose. Noise occurs at measuring Electoretinogram(ERG) signals as the other bio-signal measurement. It is compared the denoising performance according to the mother function of wavelet transforms. Methods. The ERG signal that generated power supply noise and white noise was used as a sampling signal. The noise of ERG signal was filtered by using haar, db7, bior mother function. The filtering performance of each mother functions was compared using Fourier transform spectrum and SNR(signal to noise ratio). Results. In the haar functioin, the result of the Fourier transform spectrum was that the power supply noise is removed and the white noise performance is not good. The SNR was 27.0404. In the db7 function, the results of Fourier transform spectrum was that the power supply noise is removed and the white noise performance is good. The SNR was 35.1729. In the db7 function, the results of Fourier transform spectrum was that the power supply noise is removed and the white noise performance is the bset. The SNR was 35.4445. Conclusions. The db7, bior function was good results in power supply noise and white noise filtered. The bior function is suitable for filtering noise of the ERG signal.