• Title/Summary/Keyword: 단순 적응 필터

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Multiplication Free Adaptive Digital Filter (승산을 요하지 않는 적응 디지탈 필터)

  • Park, Tae-Ho;Cha, Il-Hwan;Yun, Dae-Hui
    • The Journal of the Acoustical Society of Korea
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    • v.6 no.2
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    • pp.15-18
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    • 1987
  • Multiplication free adaptive digital filtering algorithms are discussed. The proposed. The proposed algorithm uses delta modulation digital filter and the relevant filter weights are updated using the SIGN algorithms to realize an adaptive digital filter without multiplication operations. It is shown that the resulting algorithm can be implemented using simple up/down counting operations. The convergence characteristics of the proposed adaptive digital filtering algorithm and .others are investigated for a system identification problem.

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New Video Compression Method based on Low-complexity Interpolation Filter-bank (저 복잡도 보간 필터 뱅크 기반의 새로운 비디오 압축 방법)

  • Nam, Jung-Hak;Jo, Hyun-Ho;Sim, Dong-Gyu;Choi, Byeong-Doo;Cho, Dae-Sung
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.47 no.5
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    • pp.165-174
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    • 2010
  • The H.264/AVC standard obtained better performance than previous compression standards, but it also increased the computational complexity of CODEC simultaneously. Various techniques recently included at the KTA software developed by VCEG also were increasing its complexity. Especially adaptive interpolation filter has more complexity than two times due to development for coding efficiency. In this paper, we propose low-complexity filter bank to improve speed up of decoding and coding gain. We consists of filter bank of a fixed-simple filter for low-complexity and adaptive interpolation filter for high coding efficiency. Then we compensated using optimal filter at each macroblock-level or frame-level. Experimental results shows a similar coding efficiency compared to existing adaptive interpolation filter and decoding speed of approximately 12% of the entire decoder gained.

Research on Performance Improvement of the Adaptive Active Noise Control System Using the Recurrent Neural Network (순환형 신경망을 이용한 적응형 능동소음제어시스템의 성능 향상에 대한 연구)

  • Han, Song-Ik;Lee, Tae-Oh;Yeo, Dae-Yeon;Lee, Kwon-Soon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.8
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    • pp.1759-1766
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    • 2010
  • The performance of noise attenuation of the adaptive active noise control algorithm is improved using the recurrent neural network. The FXLMS that has been frequently used in the active noise control is simple and has low computational load, but this method is weak to nonlinearity of the main or secondary path since it is based on the FIR linear filter method. In this paper, the recurrent neural network filter has been developed and applied to improvement of the active noise attenuation by simulation.

A Study on Projection Image Restoration by Adaptive Filtering (적응적 필터링에 의한 투사영상 복원에 관한 연구)

  • 김정희;김광익
    • Journal of Biomedical Engineering Research
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    • v.19 no.2
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    • pp.119-128
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    • 1998
  • This paper describes a filtering algorithm which employs apriori information of SPECT lesion detectability potential for the filtering of degraded projection images prior to the backprojection reconstruction. In this algorithm, we determined m minimum detectable lesion sized(MDLSs) by assuming m object contrasts uniformly-chosen in the range of 0.0-1.0, based on a signal/noise model which provides the capability potential of SPECT in terms of physical factors. A best estimate of given projection image is attempted as a weighted combination of the subimages from m optimal filters whose design is focused on maximizing the local S/N ratios for the MDLS-lesions. These subimages show relatively larger resolution recovery effect and relatively smaller noise reduction effect with the decreased MDLS, and the weighting on each subimage was controlled by the difference between the subimage and the maximum-resolution-recovered projection image. The proposed filtering algoritym was tested on SPECT image reconstruction problems, and produced good results. Especially, this algorithm showed the adaptive effect that approximately averages the filter outputs in homogeneous areas and sensitively depends on each filter strength on contrast preserving/enhancing in textured lesion areas of the reconstructed image.

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An Autoregressive Parameter Estimation from Noisy Speech Using the Adaptive Predictor (적응예측기를 이용하여 잡음섞인 음성신호로부터 autoregressive 계수를 추산하는 방법)

  • Koo, Bon-Eung
    • The Journal of the Acoustical Society of Korea
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    • v.14 no.3
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    • pp.90-96
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    • 1995
  • A new method for autoregressive parameter estimation from noisy observation sequence is presented. This method, termed the AP method, is a result of an attempt to make use of the adaptive predictor which is a simple and reliable way of parameter estimation. It is shown theoretically that, for noisy input, the parameter vector computed from the prediction sequence is closer to that of the original sequence than the noisy input sequence is, under the spectral distortion criterion. Simulation results with the Kalman filter as a noise reduction filter and real speech data supported the theory. Roughly speaking, the performance of the parameter set obtained by the AP method is better than noisy one but worse than the EM iteration results. When the simplicity is considered, it could provide a useful alternative to more complicated parameter estimation methods in some applications.

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An Adaptive De-blocking Algorithm in Low Bit-rate Video Coding (저 비트율 비디오를 위한 적응적 블록킹 현상 제거 기법)

  • 김종호;김해욱;정제창
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.4C
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    • pp.505-513
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    • 2004
  • Most video codecs including the international standards use the block-based hybrid structure for efficient compression. But for low bit-rate applications such as video transmission through wireless channels, the blocking artifacts degrade image qualify seriously. In this paper, we propose an adaptive de-blocking algorithm using characteristics of the block boundaries. Blocking artifacts contain the high frequency components near the block boundaries, therefore the lowpass filtering can remove them. However, simple lowpass filtering results into blurring by removing important information such as edges. To overcome this problem, we determine the modes depending upon the characteristics of pixels adjacent to block boundary then proper filter is applied to each area. Simulation results show that proposed method improves de-blocking performance compared to that of MPEG-4.

Variable Step Size LMS Algorithm Using the Error Difference (오류 차이를 활용한 가변 스텝 사이즈 LMS 알고리즘)

  • Woo, Hong-Chae
    • The Journal of the Acoustical Society of Korea
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    • v.28 no.3
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    • pp.245-250
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    • 2009
  • In communications and signal processing area, a number of least mean square adaptive algorithms have been used because of simplicity and robustness. However the LMS algorithm is known to have slow and non-uniform convergence. Various variable step size LMS adaptive algorithms have been introduced and researched to speed up the convergence rate. A variable step size LMS algorithm using the error difference for updating the step size is proposed. Compared with other algorithms, simulation results show that the proposed LMS algorithm has a fast convergence. The theoretical performance of the proposed algorithm is also analyzed for the steady state.

One Chip 반향 제거기를 위한 알고리즘 개발에 관한 연구

  • 강정신;백인천;박상봉;박노경;차균현
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.15 no.8
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    • pp.689-697
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    • 1990
  • This paper proposes ADAPTIVE STOCHASTIC ITERATION ALGORITHM that can be used for the full-duplex digital data transmission over existing twisted-pair cables. The canceller step size changes according to the residual echo level. Thus convergence speed increases by an order of magnitude over the conventional stochastic interation alogorithm. And it can be combined with the sequential type adaptive digital filter that simplifies the conventional echo canceller circuit. Thus it is suitable for LSI implementation. Theoretical analysis on two algorithms is carried out and the algorithm simulation program is developed.

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Quantization Noise Reduction in Block-Coded Video Using the Characteristics of Block Boundary Area (블록 경계 영역 특성을 이용한 블록 부호화 영상에서의 양자화 잡음 제거)

  • Kwon Kee-Koo;Yang Man-Seok;Ma Jin-Suk;Im Sung-Ho;Lim Dong-Sun
    • The KIPS Transactions:PartB
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    • v.12B no.3 s.99
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    • pp.223-232
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    • 2005
  • In this paper, we propose a novel post-filtering algorithm with low computational complexity that improves the visual quality of decoded images using block boundary classification and simple adaptive filter (SAF). At first, each block boundary is classified into smooth or complex sub-region. And for smooth-smooth sub-regions, the existence of blocking artifacts is determined using blocky strength. And simple adaptive filtering is processed in each block boundary area. The proposed method processes adaptively, that is, a nonlinear 1-D 8-tap filter is applied to smooth-smooth sub-regions with blocking artifacts, and for smooth-complex or complex-smooth sub-regions, a nonlinear 1-D variant filter is applied to block boundary pixels so as to reduce the blocking and ringing artifacts. And for complex-complex sub-regions, a nonlinear 1-D 2-tap filter is only applied to adjust two block boundary pixels so as to preserve the image details. Experimental results show that the proposed algorithm produced better results than those of conventional algorithms both subjective and objective viewpoints.

A Postfiltering Algorithm for Enhancement in Block-based DCT Compressed Images (블록 기반 DCT 압축 영상의 화질 개선을 위한 후처리 필터링 알고리듬)

  • Kim, Yong-Hun;Jeong, Jong-Hyeog
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.1
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    • pp.22-27
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    • 2014
  • Blocking and ringing artifacts continue to be the most serious defects that occur in images and video streams compressed to low bit rates using block-based discrete cosine transform(DCT) compression standards. These artifacts contain the high frequency components near the block and the edge boundaries. Usually the lowpass filter can remove them. However, simple lowpass filter results into blur by removing important information such as edges at the same time. To overcome these problems, we propose a novel postfiltering algorithm that calculate the weight value based on the intensity similarity in the neighboring pixels and multiply this weight to the Gaussian lowpass filter coefficient. Experimental results show that the proposed technique provides satisfactory performance in both objective and subjective image quality.