• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.5
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• pp.1095-1100
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• 2003

The wavelet transform pair used simultaneously when two wavelets are designed to form an approximate Hilbert transform pair provide excellent property than present DWT(discrete wavelet transform), especially in field that detect wide-band signals like pulse and increase the bit rate at the same bandwidth. In this paper, the two dyadic wavelet bases which form an approximate Hilbert transform pair were designed, and flat delay filter which has the truncated coefficient vector is used in order that the two filters can form Hilbert transform relation in the process of design.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.361-364
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• 1995

Wavelet Transform is a new tools for signal processing, such as data compressing extraction of parameter for Reconition and Diagnostics. This transform has an advandage of a good resolution compared to Fast Fourier Transform (FFT) In this study, we employ the wavelet transform for analysis of Acoustic Emission raw signal generated form rotary compressor. In abnormal condition of rotary compressor, the state of operating condition can be classified by analizing coefficient of wavelet transformed signal.

• Proceedings of the KSRS Conference
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• 2004.10a
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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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.431-434
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• 2003

As a wavelet transform which is presented as a new technique of signal processing field has time and frequency localization capabilities, it's possible for multiresolution analysis as well as easy to analyze various signal. So it is being applied in many fields recently. And when two wavelet base were designed to form Hilbert transform pair, wavelet pair show superior performance than the existing DWT(discrete wavelet transform) in data detection of pulse type. Therefore in this paper, we detected position of impulse noise by using two dyadic wavelet base which is designed by truncated coefficient vector.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.282-285
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• 2000

Three representations are known to implement the discrete wavelet transform (DWT) ; i.e., direct, lifting and matrix forms. In these representations, direct and lifting forms are well known so far. This paper derives the matrix form of the DWT from the direct form. Then, we implement these three representations on a programmable digital signal processor (in the following, DSP processor) and compare them in terms of the number of calculations and instruction cycles. As a result, we confirm that the lifting form has the lowest number of calculations and cycles, and the matrix form has an effective decrease in the number of cycles than other representations on the DSP processor.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1832-1833
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• 2006

This paper presents a design method of the wavelet neural network(WNN) controller based on a direct adaptive control scheme for the intelligent control of Autonomous Underwater Vehicle(AUV) steering systems. The neural network is constructed by the wavelet orthogonal decomposition to form a wavelet neural network that can overcome nonlinearities and uncertainty. In our control method, the control signals are directly obtained by minimizing the difference between the reference track and original signal of AUV model that is controlled through a wavelet neural network. The control process is a dynamic on-line process that uses the wavelet neural network trained by gradient-descent method. Through computer simulations, we demonstrate the effectiveness of the proposed control method.

• Journal of Mechanical Science and Technology
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• v.19 no.8
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• pp.1611-1620
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• 2005

This paper shows the use of wavelet transformation combined with inverse acoustics to reconstruct the surface velocity of a noise source. This approach uses the boundary element analysis based on the measured sound pressure at a set of field points, the Helmholtz integral equations and wavelet transformation for reconstructing the normal surface velocity field. The reconstructed field can be diverged due to the small measurement errors in the case of nearfield acoustic holography (NAH) using an inverse boundary element method. In order to avoid this instability in the inverse problem, the reconstruction process should include some form of regularization for enhancing the resolution of source images. The usual method of regularization has been the truncation of wave vectors associated with small singular values, although the order of an optimal truncation is difficult to determine. In this paper, a wavelet transformation is applied to reduce the computation time for inverse acoustics and to enhance the reconstructed vibration field. The computational speed-up is achieved, with solution time being reduced to $14.5\%$.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2414-2416
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• 2003

In this raper, we present a Wavelet Neural Network(WNN) approach to the solution of the tracking problem for mobile robots that possess complexity, nonlinearity and uncertainty. The neural network is constructed by the wavelet orthogonal decomposition to form a wavelet neural network that can overcome the problems caused by local minima of optimization and various uncertainties. This network structure is helpful to determine the number of the hidden nodes and the initial value of weights with compact structure. In our control method, the control signals are directly obtained by minimizing the difference between the reference track and the pose of a mobile robot that is controlled through a wavelet neural network. The control process is a dynamic on-line process that uses the wavelet neural network trained by the gradient-descent method. Through computer simulations, we demonstrate the effectiveness and feasibility of the proposed control method.

• Journal of Korea Multimedia Society
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• v.6 no.5
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• pp.870-875
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• 2003

We Present digital watermarking using a quadratic equation embedding method in wavelet transform domain in order to improve the invisibility. Generally, embedding watermark used a simple equation form, but we extended a quadratic equation form in this paper. We performed a computer simulation in order to compare proposed method to other methods using LENA, GOLDHILL, BARBARA, and MAN images By computer experiments, invisibility of the proposed method better than the conventional methods at 100 % normalized similarity.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.679-682
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• 2000

In this paper, a MMSE filter in homomorphic wavelet transform domain is proposed for restoring an ultrasonic images corrupted by speckle noise. In order to remove effectively the speckle noise which is a kind of multiplicative noise, speckle noise is transformed into a form of additive noise and then the additive noise is denoised through the MMSE filter in homomorphic wavelet transform domain. The proposed method shows much higher quality in terms of ISNR and subject quality.