• Title/Summary/Keyword: 비재귀형 필터

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Orthogonal Wavelet Construction using Recursive Filter Bank (재귀형 직교 웨이브렛 함수)

  • Do, Jae-Su
    • The KIPS Transactions:PartB
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    • v.8B no.4
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    • pp.395-402
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    • 2001
  • 본 논문에서는, 1차원 및 2차원 웨이브렛 함수를 전역통과필터(APF)와 지연기의 병렬접속에 위한 재귀형(IIR) 디지털 필터로 구성하는 방법을 제안한다. Mallat에 의하여 웨이브렛 변환과 필터뱅크가 밀접한 관계에 있다는 것이 알려졌고, 완전 재구성 필터뱅크로부터 웨이브렛 함수를 도출하는 다양한 방법이 알려져 있다. 그러나, 이러한 방법의 대부분은 비재귀형(FIR) 디지털 필터에 근거를 두는 것으로, 재귀형 디지털 필터에 의한 방법은 거의 제안되어 있지 않다. 재귀형 필터를 이용하는 장점은 비재귀형에 비하여 낮은 차수로 표현되는 점이다. 또 직교 웨이브렛 함수를 끌어내기 위한 직교조건을 용이하게 만족시킬 수 있다. 본 논문에서는 웨이브렛 함수에 요구되는 레귤레리티(Regularity)조건을 만족시키기 위하여, 최대 평탄성(Maximally Flat)을 부가한 새로운 1차원 및 2차원 재귀형 웨이브렛 함수의 도출법을 보인다.

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Noise Statistics Estimation Using Target-to-Noise Contribution Ratio for Parameterized Multichannel Wiener Filter (변수내장형 다채널 위너필터를 위한 목적신호대잡음 기여비를 이용한 잡음추정기법)

  • Hong, Jungpyo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.12
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    • pp.1926-1933
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    • 2022
  • Parameterized multichannel Wiener filter (PMWF) is a linear filter that can control the trade-off between residual noise and signal distortion using the embedded parameter. To apply the PMWF to noisy inputs, accurate noise estimation is important and multichannel minima-controlled recursive averaging (MMCRA) is widely used. However, in the case of the MMCRA, the accuracy of noise estimation decreases when a directional interference is involved into the array inputs. Consequently, the performance of the PMWF is degraded. Therefore, we propose a noise power spectral density (PSD) estimation method for the PMWF in this paper. The proposed method is based on a consecutive process of eigenvalue decomposition on noisy input PSD, estimation of the target component contribution using directional information, and exponential weighting for improved estimation of the target contribution. For evaluation, four objective measures were compared with the MMCRA and we verify that the PMWF with the proposed noise estimation method can improve performance in environments where directional interfereces exist.

A Study on Performance Improvement of FIR Digital Filter using Modified Window Function (변형된 창함수를 이용한 FIR 디지털 필터의 성능 향상에 관한 연구)

  • Kim, Nam-Ho;Ku, Bon-Seok
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.06a
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    • pp.758-761
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    • 2007
  • Digital signal processing technique is applied in wide fields such as speech processing, image processing and spectrum analysis. Therefore, in order to do frequency selective operation digital filter is used in stead of analog filter and sharp filter characteristics can be implemented. Since finite impulse response (FIR) digital filter as nonrecursive type represents linear phase response characteristics and is always stable and is used in fields regarding wave information importantly such as data transmission. And due to frequency characteristics, in order to remove the Gibbs phenomenon generating around a discontinuous point, filter is designed through window function method. Therefore, in this paper to improve performance of FIR digital filter, a modified window function was applied. And the proposed method was compared with conventional methods using peak side-lobe and transition properties in simulations.

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Time delay estimation by iterative Wiener filter based recursive total least squares algorithm (반복형 위너 필터 방법에 기반한 재귀적 완전 최소 제곱 방법을 사용한 시간 지연 추정 알고리즘)

  • Lim, Jun-Seok
    • The Journal of the Acoustical Society of Korea
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    • v.40 no.5
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    • pp.452-459
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    • 2021
  • Estimating the mutual time delay between two acoustic sensors is used in various fields such as tracking and estimating the location of a target in room acoustics and sonar. In the time delay estimation methods, there are a non-parametric method, such as Generalized Cross Correlation (GCC), and a parametric method based on system identification. In this paper, we propose a time delay estimation method based on the parametric method. In particular, we propose a method that considers the noise in each receiving acoustic sensor. Simulation confirms that the proposed algorithm is superior to the existing generalized cross-correlation and adaptive eigenvalue analysis methods in white noise and reverberation environments.