• Title/Summary/Keyword: Adaptive Filtering

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A study on adaptive noise cancellation for enhancement of digital speech articulation (디지털음성명료도 향상을 위한 적응형 잡음제거 기법에 관한 연구)

  • Kim, Soo-Yong;Jee, Suk-Kun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.5
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    • pp.961-968
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    • 2007
  • Today, we can use radio communication device anywhere-anytime. Sometimes, we use the device in acoustic noise environment. The acoustic noise makes many problems in communication system. In acoustic noise environment, speaker cannot send clear information to receiver, because the received signal includes both speech signal and noise signal. A digital filter is useful to remove noise to get desired signal. One of methods is the adaptive digital filter using the adaptive noise canceller that automatically adjust filter parameters. This thesis addresses articulation algorithms against actual acoustic noises by means of two adaptive filtering methods. One is the adaptive noise canceller with two input channels and another is the spectral subtraction filter with one input channel. The experimental result from the proposed filter shows that the adaptive noise canceller is useful to reduce the non-stationary noises, while the spectral amplitude filter is effective for stationary noises.

Post-filtering in Low Bit Rate Moving Picture Coding, and Subjective and Objective Evaluation of Post-filtering (저 전송률 동화상 압축에서 후처리 방법 및 후처리 방법의 주관적 객관적 평가)

  • 이영렬;김윤수;박현욱
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.8B
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    • pp.1518-1531
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    • 1999
  • The reconstructed images from highly compressed MPEG or H.263 data have noticeable image degradations, such as blocking artifacts near the block boundaries, corner outliers at cross points of blocks, and ringing noise near image edges, because the MPEG or H.263 quantizes the transformed coefficients of 8$\times$8 pixel blocks. A post-processing algorithm has been proposed by authors to reduce quantization effects, such as blocking artifacts, corner outliers, and ringing noise, in MPEG-decompressed images. Our signal-adaptive post-processing algorithm reduces the quantization effects adaptively by using both spatial frequency and temporal information extracted from the compressed data. The blocking artifacts are reduced by one-dimensional (1-D) horizontal and vertical low pass filtering (LPF), and the ringing noise is reduced by two-dimensional (2-D) signal-adaptive filtering (SAF). A comparison study of the subjective quality evaluation using modified single stimulus method (MSSM), the objective quality evaluation (PSNR) and the computation complexity analysis between the signal-adaptive post-processing algorithm and the MPEG-4 VM (Verification Model) post-processing algorithm is performed by computer simulation with several MPEG-4 image sequences. According to the comparison study, the subjective image qualities of both algorithms are similar, whereas the PSNR and the comparison complexity analysis of the signal-adaptive post-processing algorithm shows better performance than the VM post-processing algorithm.

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Adaptive CFAR Algorithm using Two-Dimensional Block Estimation (이차원 블록 추정을 이용한 적응 CFAR 알고리즘)

  • Choi Beyung Gwan;Lee Min Joon;Kim Whan Woo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.1
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    • pp.101-108
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    • 2005
  • Adaptive constant false alarm rate(CFAR) algorithm is used for good detection probability as well as constant false alarm rate in clutter background. Especially, filtering technique adaptive to spatial variation is necessary for improving detection quality in non stationary clutter environment which has spatial correlation and large magnitude deviation. In this paper, we propose a two-dimensional block interpolation(TBI) adaptive CFAR algorithm that calculates the node estimate in the fred two dimensional region and subsequently determines the final estimate for each resolution cell by two-dimensional interpolation. The proposed method is efficient for filtering abnormal ejection by adopting distribution median in fixed region and also has advantage of reducing required memory space by using estimation method which gets final values after calculating the block node values. Through simulations, we show that the proposed method is superior to the traditional adaptive CFAR algorithms which are transversal or recursive in aspect of the detection performance and required memory space.

Speech Signal Processing using Adaptative Filter (적응필터를 이용한 음성신호처리)

  • Kim, Soo-Yong;Jee, Suk-Kun;Park, Dong-Jin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.06a
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    • pp.743-749
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    • 2007
  • Today, we can use radio communication device anywhere-anytime. Sometimes, we use the device in acoustic noise environment. The acoustic noise makes many problems in communication system. In acoustic noise environment, speaker cannot send clear information to receiver, because the received signal includes both speech signal and noise signal. A digital filter is useful to remove noise to get desired signal. One of methods is the adaptive digital filter using the adaptive noise canceller that automatically adjust filter parameters. This thesis addresses articulation algorithms against actual acoustic noises by means of two adaptive filtering methods. One is the adaptive noise canceller with two input channels and another is the spectral subtraction filter with one input channel. The experimental result from the proposed filter shows that the adaptive noise canceller is useful to reduce the non-stationary noises, while the spectral amplitude filter is effective for stationary noises.

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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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    • 2001.10a
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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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A Subband Adaptive Blind Equalization Algorithm for FIR MIMO Systems (FIR MIMO 시스템을 위한 부밴드 적응 블라인드 등화 알고리즘)

  • Sohn, Sang-Wook;Lim, Young-Bin;Choi, Hun;Bae, Hyeon-Deok
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.59 no.2
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    • pp.476-483
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    • 2010
  • If the data are pre-whitened, then gradient adaptive algorithms which are simpler than higher order statistics algorithms can be used in adaptive blind signal estimation. In this paper, we propose a blind subband affine projection algorithm for multiple-input multiple-output adaptive equalization in the blind environments. All of the adaptive filters in subband affine projection equalization are decomposed to polyphase components, and the coefficients of the decomposed adaptive sub-filters are updated by defining the multiple cost functions. An infinite impulse response filter bank is designed for the data pre-whitening. Pre-whitening procedure through subband filtering can speed up the convergence rate of the algorithm without additional computation. Simulation results are presented showing the proposed algorithm's convergence rate, blind equalization and blind signal separation performances.

A New Speech Enhancement Method Using Adaptive Digital Filter (적응디지털필터를 사용한 음질향상 방법)

  • 임용훈;김완구;차일환;윤대희
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.10
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    • pp.35-41
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    • 1993
  • In this paper, a new speech enhancement method for speech signal corrupted by environmental noise is proposed. Two signals are obtained from the microphone and from the accelerometer attached to the neck, respectively. Since two signals are generated from same source signal, both signals are closely correlated. And environmental noise has no effect on the accelerometer signal. The speech enhancement system identifies the optimum linear system between two signals on the basis of the dependence between the signals. The enhanced speech can be obtained by filtering the noise-free accelerometer signal. Since the characteristcs of the speech signal and environmental noise are changing with time, adaptive filtering system has to be used for characterizing the time-varing system. Simulation results show 7dB enhancement with 0dB speech signal level relative to the white noise.

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Time Delay Estimation using Third-order Statistics and Subband Adaptive Filtering (3차 통계기법과 서브밴드 적응 필터링을 이용한 시간 지연 추정)

  • 박현석;남상원
    • Proceedings of the IEEK Conference
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    • 2001.09a
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    • pp.907-910
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    • 2001
  • In this paper, we address a new time delay estimation method using third-order statistics and subband adaptive filtering to improve the accuracy of target detection for acoustic backscattered signals in a noise interference environment. Each reference and primary signals are decorrelated using the multiresolution analysis framework through a M-band discrete wavelet transform(M-DWT). Then noise effect can be reduced. Here, time delays are estimated iteratively in each subband using two different adaptation mechanisms that minimize the mean squared error (MSE) between the references and primary signal. More specifically, third-order cumulants and projection cross-correlation(PCC) criterion are utilized to achieve an effective SNR improvement for the time delay estimation.

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Prediction of Volumes and Estimation of Real-time Origin-Destination Parameters on Urban Freeways via The Kalman Filtering Approach (칼만필터를 이용한 도시고속도로 교통량예측 및 실시간O-D 추정)

  • 강정규
    • Journal of Korean Society of Transportation
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    • v.14 no.3
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    • pp.7-26
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    • 1996
  • The estimation of real-time Origin-Destination(O-D) parameters, which gives travel demand between combinations of origin and destination points on a urban freeway network, from on-line surveillance traffic data is essential in developing an efficient ATMS strategy. On this need a real-time O-D parameter estimation model is formulated as a parameter adaptive filtering model based on the extended Kalman Filter. A Monte Carlo test have shown that the estimation of time-varying O-D parameter is possible using only traffic counts. Tests with field data produced the interesting finding that off-ramp volume predictions generated using a constant freeway O-D matrix was replaced by real-time estimates generated using the parameter adaptive filter.

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An Adaptive Dead Reckoning Algorithm using Update Lifetime (유효갱신기간에 기반한 가변 데드레코닝 알고리즘)

  • 유석종;정혜원;최윤철
    • Proceedings of the Korea Multimedia Society Conference
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    • 2000.04a
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    • pp.449-452
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    • 2000
  • This paper proposes a new, adaptive Dead Reckoning model, called Dynamic Dead Reckoning , for Distributed Interactive Simulation and humanoid avatar systems. The proposed model can overcome the weak points of traditional Dead Reckoning caused by a fixed threshold and strong dependency on rotation event. This paper introduces new criteria for update message filtering , named as Update lifetime. The Dynamic Dead Reckoning keeps the balance between extrapolation fidelity and filtering performance by two component models, Variable Threshold Mechanism and Rotation Event model. The experimental results show that the proposed model can lower the increment rate of update traffic to the increase of rotation frequency without any significant loss of accuracy.

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