• 한국산학기술학회논문지
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• 제14권8호
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• pp.3983-3991
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• 2013

스테레오 매칭 중 센서스 변환은 방사 왜곡과 밝기 변화에 강한 특징이 있다. 본 논문은 미니 센서스 변환과 일반화된 센서스 변환을 동시에 이용한 하이브리드 센서스 변환을 제안하였다. 제안한 하이브리드 센서스 변환 방법은 미니 센서스 변환의 적은 계산량과 일반화된 센서스 변환의 잡음에 강인한 특성을 반영하여 설계되었다. 성능을 평가하기 위하여 후처리 과정까지 포함하여 스테레오 매칭을 수행하였다. 그 결과 하이브리드 센서스 변환은 일반화된 센서스 변환과 성능이 비슷하였고, 계산량은 미니 센서스 변환과 일반화된 센서스의 중간값을 갖는다.

• 방송공학회논문지
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• 제28권1호
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• pp.100-108
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• 2023

하이브리드 블록 기반 비디오 압축에서 변환 부호화는 공간 영역의 잔차 신호를 주파수 영역으로 변환하여 낮은 주파수 대역에 에너지를 집중시켜 이후 엔트로피 코딩 과정에서 높은 압축률을 달성할 수 있게 한다. 최신 비디오 압축 표준인 VVC(Versatile Video Coding)는 DCT-2(Discrete Cosine Transform type 2), DST-7(Discrete Sine Transform type 7), DCT-8(Discrete Cosine Transform type 8)를 사용하여 주변환을 수행한다. 본 논문에서는 DCT-2, DST-7, DCT-8이 모두 선형 변환임을 고려하여, 선형 변환의 선형성을 이용하여 역변환 시 곱셈 연산량을 줄이는 역변환 방법을 제안한다. 제안하는 역변환 방법은 VVC의 참조 소프트웨어인 VVC Test Model-8.2 (VTM-8.2) 대비 비트율의 증가 없이 부호화 시간과 복호화 시간이 AI(All Intra)에서 평균 26%, 15%, RA(Randon Access)에서 평균 4%, 10% 감소하였다.

• 대한수학회지
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• 제49권5호
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• pp.1065-1082
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• 2012

In this paper we first investigate the existence of the generalized Fourier-Feynman transform of the functional F given by $$F(x)={\hat{\nu}}((e_1,x)^{\sim},{\ldots},(e_n,x)^{\sim})$$, where $(e,x)^{\sim}$ denotes the Paley-Wiener-Zygmund stochastic integral with $x$ in a very general function space $C_{a,b}[0,T]$ and $\hat{\nu}$ is the Fourier transform of complex measure ${\nu}$ on $B({\mathbb{R}}^n)$ with finite total variation. We then define two sequential transforms. Finally, we establish that the one is to identify the generalized Fourier-Feynman transform and the another transform acts like an inverse generalized Fourier-Feynman transform.

• 충청수학회지
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• 제35권2호
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• pp.177-196
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• 2022

The Elzaki Transform method is fuzzified to fuzzy Elzaki Transform by Rehab Ali Khudair. In this article, we propose a Double fuzzy Elzaki transform (DFET) method to solving fuzzy partial differential equations (FPDEs) and we prove some properties and theorems of DFET, fundamental results of DFET for fuzzy partial derivatives of the n^th order, construct the Procedure to find the solution of FPDEs by DFET, provide duality relation of Double Fuzzy Laplace Transform (DFLT) and Double Fuzzy Sumudu Transform(DFST) with proposed Transform. Also we solve the Fuzzy Poisson's equation and fuzzy Telegraph equation to show the DFET method is a powerful mathematical tool for solving FPDEs analytically.

• Journal of Information Processing Systems
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• 제12권4호
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• pp.754-764
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• 2016

The exhaustive list of sparsification methods for a digital image suffers from achieving an adequate number of zero and near-zero coefficients. The method proposed in this paper, which is known as the Discrete Rajan Transform Sparsification, overcomes this inadequacy. An attempt has been made to compare the simulation results for benchmark images by various popular, existing techniques and analyzing from different aspects. With the help of Discrete Rajan Transform algorithm, both lossless and lossy sparse representations are obtained. We divided an image into $8{\times}8-sized$ blocks and applied the Discrete Rajan Transform algorithm to it to get a more sparsified spectrum. The image was reconstructed from the transformed output of the Discrete Rajan Transform algorithm with an acceptable peak signal-to-noise ratio. The performance of the Discrete Rajan Transform in providing sparsity was compared with the results provided by the Discrete Fourier Transform, Discrete Cosine Transform, and the Discrete Wavelet Transform by means of the Degree of Sparsity. The simulation results proved that the Discrete Rajan Transform provides better sparsification when compared to other methods.

• 전자공학회논문지
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• 제53권4호
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• pp.106-114
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• 2016

본 논문에서는 VP9 디코더에 대한 행렬 기반의 정수형 역변환 구조를 제안한다. 제안하는 구조는 DCT(Discreste Cosine Transform), ADST(Asymmetric Discrete Sine Transform) 그리고 WHT(Walsh-Hadamard Transform)에 대한 알고리즘을 공유하며 버터플라이구조보다 하드웨어 리소스를 줄이고 제어하기 쉬운 하드웨어 구조이다. VP9 구글 모델 내 정수형 역변환은 버터플라이구조 기반의 정수형 역변환 구조를 가진다. 일반적인 버터플라이구조와는 달리 구글모델 내 정수형 역변환은 각 단계마다 라운드 쉬프트 연산기를 가지며, 비대칭 구조의 사인 변환을 포함한다. 따라서 제안하는 구조는 모든 역변환 모드에 대해 행렬계수 값을 근사하고, 이 계수 값을 이용하여 행렬연산 방식을 사용한다. 본 논문의 기술을 사용하면 역변환 알고리즘에 대한 모드별 동작 공유 및 버터플라이구조에 비해 곱셈기 수를 2배가량 감소시킬 수 있다. 그래서 하드웨어 리소스를 효율적으로 관리가 가능해진다.

• The Journal of the Acoustical Society of Korea
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• 제15권3E호
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• pp.74-77
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• 1996

In this paper we implement the Discrete Rotational Fourier Transform(DRFT) which is a discrete version of the Angular Fourier Transform and its inverse transform. We simplify the computation algorithm in [4], and calculate the complexity of the proposed implementation of the DRFT and the inverse DRFT, in comparison with the complexity of a DFT (Discrete Fourier Transform).

• 디지털산업정보학회논문지
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• 제11권1호
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• pp.171-182
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• 2015

The general wavelet transform has profitable property in non-stationary signal analysis specially. The tunable Q-factor wavelet transform is a fully-discrete wavelet transform for which the Q-factor Q and the asymptotic redundancy r, of the transform are easily and independently specified. In particular, the specified parameters Q and r can be real-valued. Therefore, by tuning Q, the oscillatory behavior of the wavelet can be chosen to match the oscillatory behavior of the signal of interest, so as to enhance the sparsity of a sparse signal representation. The TQWT is well suited to fast algorithms for sparsity-based inverse problems because it is a Parseval frame, easily invertible, and can be efficiently implemented. The transform is based on a real valued scaling factor and is implemented using a perfect reconstruction over-sampled filter bank with real-valued sampling factors. The transform is parameterized by its Q-factor and its over-sampling rate, with modest over-sampling rates being sufficient for the analysis/synthesis functions to be well localized. This paper describes filter design of 2D discrete-time wavelet transform for which the Q-factor is easily specified. With the advantage of this transform, perfect reconstruction filter design and implementation for performance improvement are focused in this paper. Hence, the 2D transform can be tuned according to the oscillatory behavior of the image signal to which it is applied. Therefore, application for performance improvement in multimedia communication field was evaluated.

• 디지털산업정보학회논문지
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• 제10권3호
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• pp.237-247
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• 2014

This paper describes a 2D discrete-time wavelet transform for which the Q-factor is easily specified. Hence, the transform can be tuned according to the oscillatory behavior of the image signal to which it is applied. The tunable Q-factor wavelet transform (TQWT) is a fully-discrete wavelet transform for which the Q-factor, Q, of the underlying wavelet and the asymptotic redundancy (over-sampling rate), r, of the transform are easily and independently specified. In particular, the specified parameters Q and r can be real-valued. Therefore, by tuning Q, the oscillatory behavior of the wavelet can be chosen to match the oscillatory behavior of the signal of interest, so as to enhance the sparsity of a sparse signal representation. The TQWT is well suited to fast algorithms for sparsity-based inverse problems because it is a Parseval frame, easily invertible, and can be efficiently implemented. The TQWT can also be used as an easily-invertible discrete approximation of the continuous wavelet transform. The transform is based on a real valued scaling factor (dilation-factor) and is implemented using a perfect reconstruction over-sampled filter bank with real-valued sampling factors. The transform is parameterized by its Q-factor and its oversampling rate (redundancy), with modest oversampling rates (e. g. 3-4 times overcomplete) being sufficient for the analysis/synthesis functions to be well localized. Therefore, This method services good performance in image processing fields.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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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.