• Journal of the Institute of Convergence Signal Processing
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• v.2 no.1
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• pp.19-27
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• 2001

The conventional fractal image compression based on wavelet transform has the disadvantage that the encoding takes many time, since it finds the optimum domain for all the range blocks. In this paper, we propose the fractal image compression based on wavelet transform using the SAS(Self Affine System) techniques. It consists of the range and domain blocks in the wavelet transform, and the range blocks select the domain which is located the relatively same position. In the encoding process, the proposed methods introduce SAS techniques that the searching process of the domains blocks is not required. Therefore, it can perform a fast encoding by reducing the computational complexity. And, the image quality is improved using the different scale factors for each level and the sub-tree in the decoding. As a result, the image quality and the compression ratio are adjustable by the scale factors.

• Journal of Broadcast Engineering
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• v.15 no.3
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• pp.355-361
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• 2010

Video Compression is the key technology for the transmission of multi-media data. Because the Motion Estimation is the most complex module in the video compression, fast motion estimation algorithm is essential for the real-time application. In this paper, we propose an enhanced binary motion estimation algorithm based on the wavelet transform. Proposed algorithm improve the quality of coded video.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.594-596
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• 1999

It is extremely important to compress a very large multimedia data under the currently used communication networks because of the forthcoming high fast multimedia informations. Wavelets are very popular and useful mathematical tool in the field of signal processing recently. In this paper, signal compression methods using the wavelet packet transform are compared with the other compression method under same threshold condition. As the result, the compression of using the wavelet packet transform is much more effective than the other compressing methods.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1015-1018
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• 2002

We show how any discrete wavelet transform or two band subband filtering with finite filters can be decomposed onto a finite sequence of simple filtering steps, which we call lifting steps but that are also known as ladder structures, We present a self-contained derivations, building the decomposition from the basic principles such as the Euclidean algorithm, with a focus on a applying it to wavelet filtering. This factorization provides an alternative for the lattice factorization, with the advantage that it can also be used in the bi-orthogonal, i.e, non-unitary case. Lifting leads to a speed-up when compared to the standard implementation. We show that this lifting scheme can be applied in image compression efficiently

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.351-355
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• 1999

The amount of data stored, processed and transmitted in the multi-media systems has been growing very fast, especially for the image data. For example, it takes 0.75Mbytes to store 512 12 pixels of 24-bit color image. A video signal with 30 frames per second will require 22.5Mbytes of storage space. To solve this problem, we need a good image compression technique. Recently, many researches on the image compression technique based on the wavelet transform are being pursued to overcome the problems of traditional JPEG. This paper describes the architecture and design of two-dimensional wavelet transform circuit. To keep the sire of the circuit small, we tried to minimize the internal storage space by using external SDRAM. This circuit was designed in Verilog-HDL, synthesized using Design Compiler and verified using Verilog-XL.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1901-1906
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• 2010

This classification of walking patterns is important and many kinds of applications. Therefore, we attempted to classify walking on level ground from slow walking to fast walking using a waist acceleration signal. A tri-axial accelerometer was fixed to the subject's waist and the three acceleration signals were recorded by bluetooth module at a sampling rate of 100 Hz eleven healthy. The data were analyzed using discrete wavelet transform. Walking patterns were classified using two parameters; One was the ratio between the power of wavelet coefficients which were corresponded to locomotion and total power in the anteroposterior direction (RPA). The other was the ratio between root mean square of wavelet coefficients at the anteroposterior direction and that at the vertical direction(RAV). Slow walking could be distinguished by the smallest value in RPA from other walking pattern. Fast walking could be discriminated from level walking using RAV. It was possible to classify the walking pattern using acceleration signal in healthy people.

• Proceedings of the KIPE Conference
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• 2020.08a
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• pp.1-3
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• 2020

본 논문은 주파수 분석 방법 중 하나인 Discrete Wavelet Transform (DWT)을 활용하여 태양광 직렬 아크 사고를 검출하는 방법에 관하여 다룬다. DWT 알고리즘은 주파수 도메인에서도 시간 축 정보를 표현할 수 있어 기존의 Fast Fourier Transform (FFT) 주파수 분석 알고리즘과 차이점이 있으며, 대용량 태양광 시스템의 직렬 아크 사고 검출에 최적화 되도록 DWT 알고리즘의 속도를 향상시켜 태양광 DC 아크 사고 안전규격인 UL1699B의 요구 조건을 만족시켰다. DWT 알고리즘의 경우 TMS320F28033 기반으로 구현 되었으며 대용량 PV 시스템 적용을 위해 로고스키코일을 전류 센서로 사용하였다. 또한, 모의 DC 직렬 아크 발생 회로를 구축하여 제작한 사고 검출기의 성능을 실제 아크 발생 조건에서 검증하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.2
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• pp.461-468
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• 2000

Amounts of audio data used in several computer application have necessitated the development of audio database systems with newer features such as content-based queries and similarity searches to manage and use such data. Fast and accurate retrievals for content-based queries are crucial for such systems to be useful. Efficient content-based indexing and similarity searching schemes are keys to providing fast and relevant data retrievals. This paper present a method for indexing of Korean Traditional Music audio data based on wavelets. Also this paper present possibility of wavelet based audio indexing.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.70-71
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• 1998

In this paper, We proposed fast ultrasound image compression based on characteristics of ultrasound images. In the proposed method, wavelet transform is performed for non-zero coefficients selectively. It codes zero-tree symbols using conditional pdf (probability density function) as orientation of bands. It normalizes wavelet coefficients with threshold of each wavelet band and encodes those using a uniform quantizer. Experimental results show that the proposed method is the proposed method is superior in PSNR to LuraTech's method by about 1.0 dB, to JPEG by about 5.0 dB for $640\times480$ 24bits color ultrasound image.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2254-2259
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• 2005

In this paper, we propose a wavelet based fuzzy neural network(WFNN) based direct adaptive control scheme for the solution of the tracking problem of mobile robots. To design a controller, we present a WFNN structure that merges advantages of neural network, fuzzy model and wavelet transform. The basic idea of our WFNN structure is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. In our control system, the control signals are directly obtained to minimize the difference between the reference track and the pose of mobile robot using the gradient descent(GD) method. In addition, an approach that uses adaptive learning rates for the training of WFNN controller is driven via a Lyapunov stability analysis to guarantee the fast convergence, that is, learning rates are adaptively determined to rapidly minimize the state errors of a mobile robot. Finally, to evaluate the performance of the proposed direct adaptive control system using the WFNN controller, we compare the control performance of the WFNN controller with those of the FNN, the WNN and the WFM controllers.