• 제목/요약/키워드: adaptive Volterra filter

검색결과 18건 처리시간 0.028초

Hybrid Adaptive Volterra Filter Robust to Nonlinear Distortion

  • Kwon, Oh-Sang
    • The Journal of the Acoustical Society of Korea
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    • 제27권3E호
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    • pp.95-103
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    • 2008
  • In this paper, the new hybrid adaptive Volterra filter was proposed to be applied for compensating the nonlinear distortion of memoryless nonlinear systems with saturation characteristics. Through computer simulations as well as the analytical analysis, it could be shown that it is possible for both conventional Volterra filter and proposed hybrid Volterra filter, to be applied for linearizing the memoryless nonlinear system with nonlinear distortion. Also, the simulations results demonstrated that the proposed hybrid filter may have faster convergence speed and better capability of compensating the nonlinear distortion than the conventional Volterra filter.

부대역 비선형 Volterra 적응필터의 응용과 성능분석 (Applications and analysis on the subband nonlinear adaptive Volterra filter)

  • 양윤기;변희정
    • 전기전자학회논문지
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    • 제17권2호
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    • pp.111-118
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    • 2013
  • 본 논문에서는 부대역 신호를 사용한 병렬 적응 비선형 Volterra 필터를 소개하고, 이 시스템의 성능을 분석하는 것을 주요 내용으로 한다. 연구 결과 제시한 부대역 신호를 사용한 적응 Volterra 필터는 수렴성이 우수함을 입력신호의 상관함수의 eigenvalue 분포를 사용하여 해석적으로 도출되었으며, 이러한 응용이 최근에 보고된 적응 반향 제거기에서 유용하게 사용될 수 있음을 이론적으로 밝혔다. 또한 각 부대역 에서의 최적필터를 이론적으로 유도하였고 컴퓨터 모의실험으로 이를 검증하였다.

주파수영역LMS 2차 적수Volterra 필터와 그 분석 (The Frequency-Domain LMS Second-order Adaptive Volterra Filter and Its Analysis)

  • 정익주
    • 한국음향학회지
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    • 제12권1호
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    • pp.37-46
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    • 1993
  • The adaptive algorithm for the Volterra filter is considered. Owing to its simplicity, the LMS algorithm for adaptive Volterra filter(AVF) is widely used as in linear adaptive filters. However, the convergence speed is unsatisfactory. For improving the convergence speed, the frequency domain LMS second order adaptive Volterra filter(FLMS-AVF) is proposed and analyzed. We show that the time and frequency domain LMS AVF's have the same steady state performance under approprate conditons. Moreover, it can be shown that this algorithm can improve the convergence speed significantly by applying self-orthogonalizing method.

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볼테라 필터를 이용한 디지털 통신 채널의 적응 비선형 보상기법 (Adaptive nonlinear compensation of digital communication channels using a volterra filter)

  • 김진영;최봉준;남상원
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.16-19
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    • 1996
  • The objective of this paper is to present a new adaptive nonlinear compensation method, which is based upon the Pth-order inverse theory and can be implemented in a systematic way, for weakly nonlinear systems that can be modeled by a Volterra series. In particular, employment of the proposed approach for the linearization of a given nonlinear system leads to the effective elimination of (up to a required order) nonlinearities in the overall system output. To demonstrate the feasibility of the proposed method, simulation results using a satellite communication system model are also provided.

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적응 2차 볼테라 필터의 효율적인 구현 (The effective implementation of adaptive second-order Volterra filter)

  • 정익주
    • 전기전자학회논문지
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    • 제24권2호
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    • pp.570-578
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    • 2020
  • 본 논문에서는 적응 2차 볼테라 필터를 효율적으로 구현할 수 있는 새로운 방법을 제안한다. 연산량 감소를 위해 제안된 UCFD-SVF는 수렴 성능이 저하되는 단점이 있다. UCFD-SVF의 적응 필터 계수가 적응이 진행되면서 그 에너지가 급격하게 증가하지 않는다는 점을 이용하여 적응 필터 계수를 주기적으로 초기화는 방법을 제안하였다. 또한 일정한 수렴 성능을 보장하기 위해 가변적인 간격으로 적응 필터 계수를 초기화하는 방법을 제안하였고, 비정상 환경에서 우수한 수렴 특성을 가짐을 적응 시스템 확인 응용을 위한 컴퓨터 모의 실험을 통해 보였다.

Design of an Adaptive Nonlinear Compensator using a Wavelet Transform Domain Volterra Filter and a Modified Escalator Algorithm

  • Hwang, Dong-Oh;Kang, Dong-Jun;Nam, Sang-Won
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.98.5-98
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    • 2001
  • An efficient adaptive nonlinear compensator, based on a wavelet transform domain adaptive Volterra filter along with a modified escalator algorithm, is proposed to speed up the convergence rate of an adaptive LMS algorithm. In particular, it is well known that the e.g., slow convergence speed of an adaptive LMS algorithm depends on the statistical characteristics (e.g., large eigenvalue spread) of the corresponding auto-correlation matrix of the input vector. To solve such a convergence problem, the proposed approach utilizes a modified escalator algorithm and a wavelet transform domain adaptive LMS Volterra filtering technique, which leads to diagonalization of the auto-correlation matrix of the ...

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3차 볼테라 시스템의 선형화를 위한 적웅 선행처리 기법 (On the Adaptive Pre-processing Technique for the Linearization of a Third-Order Volterra System)

  • 김진영;최봉준;남상원
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1996년도 하계학술대회 논문집 B
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    • pp.1289-1291
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    • 1996
  • In this paper, we propose a new adaptive pre-processing technique for the linearization of a weakly nonlinear system which can be modeled by a Volterra series up to third order. To compensate the nonlinear effects of a given system, an update algorithm for the linear filter coefficients of the proposed adaptive pre-processor is introduced, and to compensate the linear distortion of the given system, the linear inverse filter is also utilized. For the performance test of the proposed adaptive pre-processor, computer simulation results obtained by analyzing an ANRSS loudspeaker model are provided.

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음향 피드백 경로를 가진 2차 볼테라 시스템의 능동소음제어 (Active noise control of a second-order Volterra system with an acoustic feedback path)

  • 이정재;김경재;서재범;남상원
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2008년도 심포지엄 논문집 정보 및 제어부문
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    • pp.238-239
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    • 2008
  • In this paper, active noise control (ANC) of a Volterra system with a nonlinear secondary path is proposed in the presence of a linear acoustic feedback, whereby the conventional ANC of a linear system with online acoustic feedback-path modeling is further extended to ANC of a Volterra system with a linear acoustic feedback path. In particular, the proposed ANC system consists of two adaptive Volterra filters (for nonlinear noise control and nonlinear adaptive noise cancellation) and one feedback-path modeling filter. Simulation results show that the proposed approach yields more effective reduction of disturbances arising from the acoustic feedback, in addition to high nonlinear ANC performance.

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효과적인 적응 전처리왜곡기를 이용한 OFDM 시스템에서의 비선형 왜곡 보상 (On Compensating Nonlinear Distortions of an OFDM System Using an Efficient Adaptive Predistorter)

  • 강현우;조용수;윤대희
    • 한국통신학회논문지
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    • 제22권4호
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    • pp.696-705
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    • 1997
  • This paper presents an efficient adaptive predistortion technique compensating linear and nonlinear distortions caused by high-power amplifier (HPA) with memory in OFDM systems. The efficient adaptive data predistortion techniques proposed for compensation of HPA with memory in single carrier systems cannot be applied to OFDM systems since the possible input levels for HPA is infinite in OFDM systems. Also, previous adaptive predistortion techniques, based on Volterra series modeling, are not suitable for real-time implementation due to high computational burden and slow convergence rate. In the proposed approach, the memoryless HPA preceded by a linear filter in OFDM systems is modeled by the Wiener system which is then precompensated by the proposed adaptive predistorter with a minimum number of filter taps. An adaptive algorithm for adjusting the proposed adaptive predistorter is derived using the stochastic gradient method. It is demonstrated by computer simulation that the performance of OFDM system suffering from nonlinear distortion can be greatly improved by the proposed efficient adaptive predistorter using a small number of filter taps.

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피드백 구조의 적응 RF 필터를 이용한 EEG 신호 예측 (EEG Signal Prediction Using Feedback Structured Adaptive RF Filter)

  • 김현술;우용호;김택수;최윤호;박상희
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1995년도 추계학술대회
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    • pp.282-285
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    • 1995
  • In this paper, we present a feedback structured adaptive RF filter based on the recursive modified Gram-Schmidt algorithm for short-term prediction of EEG signal. And the performance of this proposed filter is compared with those of linear AR model, RF filter, Volterra filter and RBF neural network as single-step prediction and multi-step prediction. The results show the superiority of this proposed filter in prediction of EEG signals.

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