• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1215-1221
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• 1999

A high speed digital distance relaying algorithm based on a Wavelet Transformation is proposed. To obtain stable phasor values very quickly, first, a lowpass filter which has low cutoff frequency is used. Secondly, db2(Daubechies 2) Wavelet which has the data window of 4 samples is used. A FIR filter which removes the DC-offset component in current relaying signals is applied. In accordance with a series of tests, the operation time of the relaying algorithm is less than 3/4 cycles after faults in a 80 [km], 154[kV], 60[Hz] over-head transmission line system.

• The Journal of Information Technology
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• v.2 no.2
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• pp.127-138
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• 1999

The wavelet transform is widely used in signal processing application. In this paper, a wavelet domain adaptive algorithm(WPTNLMS) is derived and its performances are evaluated in non-stationary environment. Where the input signals are decomposed by the wavelet packet transform for the multi-resolution adaptive processing. And the NLMS is used as an adaptive algorithm in wavelet domain. The proposed technique is applied to noise cancellation of the Doppler signal which is added with white Gaussian noise.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.269-273
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• 2000

This paper describes Active Noise Control (ANC) using Discrete Wavelet Transform (DWT) Domain Least Mean Square (LMS) Method. DWT-LMS is one of the transform domain input decorrelation LMS and improves the convergence speed of adaptive filter especially when the input signal is highly correlated. Conventional transform domain LMS's use Discrete Cosine Transform (DCT) because it offers linear band signal decomposition and fast transform algorithm. Wavelet transform can project the input signal into the several octave band subspace and offers more efficient sliding fast transform algorithm. In this paper, we propose Wavelet transform domain LMS algorithm and shows its performance is similar to DCT LMS in some cases using ANC simulation.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.4
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• pp.338-342
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• 2000

In order to approximate a nonlinear function, wacelet neural networks combining wacelet theory and neural networks have been proposed as an alternative to conventional multi-layered neural networks. wacelet neural networks provide better approximating performance than conventional neural networks. In this paper, an effective method to construct an optimal wavelet neural network is proposed using genetic alogorithm. Genetic Algorithm is used to determine dilationa and translations of wavelet basic functions of wavelet neural networks. Then, these determined dilations dilations and translations, wavelet neural networks are funther trained by back propagation learning algorithm. The effectiveness of the final network is verified thrifigh the approximation result of a nonlinear function and comparison with conventional neural networks.

• Journal of Navigation and Port Research
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• v.26 no.2
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• pp.209-213
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• 2002

MRA(Multi-resolution analysis) algorithm by Wavelet and morphology with $3{\times}3$ SQ(square) SE(structure element) is efficient to remove ship's radar clutter progressively and enhances detecting performance. Smoothing efficiency of RMM (Recursive mathematical Morphology) is better than that of Morphology. So, to get a better result than that of old algorithms, this paper proposes a new MRA algorithm which uses Wavelet and Recursive mathematical Morphology with $3{\times}3$ RHR(rhombus) SE. Simulation result of the proposed algorithm shows that PSNR is 0.65~1.50db better than that of old method.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.225-228
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• 1996

ECG data are used for the diagnostic purposes with many clinical situations, especially heart disease. In this paper, an efficient ECG data compression technique by wavelet transform and high-speed vector quantization on PMS-B algorithm is proposed. In general, ECG data compression techniques are divided into two categories: direct and transform methods. The direct data compression techniques are AZTEC, TP, CORTES, FAN and SAPA algorithms, besides the transform methods include K-L, Fourier, Walsh, and wavelet transforms. In this paper, we applied wavelet analysis to the ECG data. In particular, vector quantization on PMS-B algorithm to the wavelet coefficients in the higher frequency regions, but scalar quantized in the lower frequency regions by PCM. Finally, the quantized indices were compressed by LZW lossless entropy encoder. As the result of simulation, it turns out to get sufficient compression ratio while keeping clinically acceptable PRD.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.785-792
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• 2004

In this paper, we propose a fast and efficient method that improves the performance of embedded zerotree wavelet(EZW) algorithm introduced by Sharipo． In the EZW algorithm, two bits are allocated for a symbol, but it is inefficient for compression and the zerotree coding wastes much time at encoding. In this paper, in order to increase the efficiency of compression, it will be allocated a variable bit for a symbol at each subband. To reduce the encoding time, we use a backscan method and lifting scheme instead of filter bank in wavelet transform. Experimental result are shown that the algorithm suggested in this paper has a better performance about 0.3∼1.5㏈ PSNR while the encoding time was speeded up more than 2-10 times compared with the EZW algorithm.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1697-1708
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• 2017

This paper proposes an algorithm for the differential protection of an Indirect Symmetrical Phase Shift Transformer (ISPST) by considering the different behaviors of the compensated differential current under internal fault and magnetizing inrush conditions. In this algorithm, a criterion function is defined which is based on the difference of amplitude of the wavelet transformation over a specific frequency band. The function has been used for the discrimination between three phase magnetizing inrush and internal fault condition and requires less than a quarter cycle after disturbance. This method is independent of any coefficient or threshold values of wavelet transformation. The merit of this algorithm is demonstrated by the simulation of different faults in series and excitation unit and magnetizing inrush with varying switching conditions on ISPST using PSCAD/EMTDC. Due to unavailability of in-field large interconnected transformers for such a large number of destructive tests, the results are further verified by Real Time Digital Simulator (RSCAD/RTDS). The proposed algorithm has been compared with the conventional harmonic restraint based method that justifies the application of wavelet transform for differential protection of ISPST. The proposed algorithm has also been verified for different rating of ISPSTs and satisfactory results were obtained.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.5
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• pp.390-395
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• 2000

We present a fingerprint identification algorithm using the wavelet transform and correlation. The wavelet transform is used because of its simple operation to extract fingerprint minutiaes features for fingerprint classification. We perform the rowwise 1-D wavelet transform for a $256\times256$ fingerprint image to get a $1\times256$ column vector using the Haar wavelet and repeat 1-D wavelet transform for a 1$\times$256 column vector to get a $1\times4$ feature vector. Using PNN(Probabilistic Neural Network), we select the possible candidates from the stored feature vectors for fingerprint images. For those candidates, we compute the correlation between the input binary image and the target binary image to find the most similar fingerprint image. The proposed algorithm may be the key to a low cost fingerprint identification system that can be operated on a small computer because it does not need a large memory size and much computation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.11
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• pp.673-679
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• 2005

This Paper presents the 3D wavelet transformation based video compression system, which possesses the capability of progressive transmission by increasing resolution and increasing rate for multimedia applications. The 3D wavelet packet based video compression system removes the temporal correlation of the input sequences using the motion compensation filter and decomposes the spatio-temporal subband using the spatial wavelet packet transformation. The proposed system allocates the higher bit rate to the low frequency image of the 3D wavelet sequences and improves the 0.49dB PSNR performance of the reconstructed image in comparison with that of H.263. In addition to the limitation on the propagation of the motion compensation error by the 3D wavelet transformation, the proposed system progressively transmits the input sequence according to the resolution and rate scalability.