• Title/Summary/Keyword: Adaptive weighted filter

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Multi-channel Active Noise Control Using Subband Hybrid Adaptive Filters (서브밴드 하이브리드 적응필터를 이용한 다중채널 능동소음제어)

  • 남현도;김덕중;박용식
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.14 no.1
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    • pp.94-101
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    • 2000
  • In this paper, a multi-channel active noise control(ANC) system using subband hybrid control techniques is proposed. Subband techniques could reduce computational burden and improve the performance of ANC systems by dividing several frequency subband and adjusting adaptive filter coefficients. So it can effectively cancel noises at wanted frequency range and use lower order adaptive filter than the existing algorithms. The adjoint LMS algorithm, which prefilter the error signals instead of the divided reference signals in frequency band, is also used for adaptive filter algorithms to reduce the computational burden of the subband adaptive systems. To improve performance of the ANC system, a weighted hybrid control technique, which has weightily properties of feedforward control systems and feedback control systems, is applied. This algorithm shows higher stability and good noise attenuation property in broad band ANC systems. Computer simulations were performed to show the effectiveness of the proposed algorithm.

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Face and Hand Tracking using MAWUPC algorithm in Complex background (복잡한 배경에서 MAWUPC 알고리즘을 이용한 얼굴과 손의 추적)

  • Lee, Sang-Hwan;An, Sang-Cheol;Kim, Hyeong-Gon;Kim, Jae-Hui
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.2
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    • pp.39-49
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    • 2002
  • This paper proposes the MAWUPC (Motion Adaptive Weighted Unmatched Pixel Count) algorithm to track multiple objects of similar color The MAWUPC algorithm has the new method that combines color and motion effectively. We apply the MAWUPC algorithm to face and hand tracking against complex background in an image sequence captured by using single camera. The MAWUPC algorithm is an improvement of previously proposed AWUPC (Adaptive weighted Unmatched Pixel Count) algorithm based on the concept of the Moving Color that combines effectively color and motion information. The proposed algorithm incorporates a color transform for enhancing a specific color, the UPC(Unmatched Pixel Count) operation for detecting motion, and the discrete Kalman filter for reflecting motion. The proposed algorithm has advantages in reducing the bad effect of occlusion among target objects and, at the same time, in rejecting static background objects that have a similar color to tracking objects's color. This paper shows the efficiency of the proposed MAWUPC algorithm by face and hands tracking experiments for several image sequences that have complex backgrounds, face-hand occlusion, and hands crossing.

MULTIDIMENSIONAL INTERPOLATIONS FOR THE HIGH ORDER SCHEMES IN ADAPTIVE GRIDS (적응 격자 고차 해상도 해법을 위한 다차원 내삽법)

  • Chang, S.M.;Morris, P.J.
    • Journal of computational fluids engineering
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    • v.11 no.4 s.35
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    • pp.39-47
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    • 2006
  • In this paper, the authors developed a multidimensional interpolation method inside a finite volume cell in the computation of high-order accurate numerical flux such as the fifth order WEND (weighted essentially non-oscillatory) scheme. This numerical method starts from a simple Taylor series expansion in a proper spatial order of accuracy, and the WEND filter is used for the reconstruction of sharp nonlinear waves like shocks in the compressible flow. Two kinds of interpolations are developed: one is for the cell-averaged values of conservative variables divided in one mother cell (Type 1), and the other is for the vertex values in the individual cells (Type 2). The result of the present study can be directly used to the cell refinement as well as the convective flux between finer and coarser cells in the Cartesian adaptive grid system (Type 1) and to the post-processing as well as the viscous flux in the Navier-Stokes equations on any types of structured and unstructured grids (Type 2).

A Weighted Block Adaptive Estimation for STBC Single-Carrier System in Frequency-Selective Time-Varying Channels (다중 경로 시변 채널 환경에서 시공간 블록 부호 단일 반송파 시스템을 위한 가중치 블록 적응형 채널 추정 알고리즘)

  • Baek, Jong-Seob;Kwon, Hyuk-Jae;Seo, Jong-Soo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.3C
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    • pp.338-347
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    • 2007
  • In this paper, a weighted block adaptive channel estimation (WBA-CE) for a space-time block-coded (STBC) single-carrier transmission with a cyclic-prefix is proposed. In operation of the WBA-CE, a STBC matrix-wise block for filter input symbols is first formulated. Applying a weighted a posteriori error vector-based least-square (LS) criterion for this block, the coefficient correction terms of the WBA-CE are then computed. An approximate steady-state excess mean-square error (EMSE) of the WBA-CE for the stationary optimal coefficient is also analyzed. Simulation results show in a time-varying typical urban (TU) channel that the proposed channel estimator provides better bit-error-rate (BER) performances than conventional algorithms such as the NLMS and RLS channel estimators.

Adaptive Formulation of the Transition Matrix of Markovian Mobile Communication Channels

  • Park, Seung-Keun
    • The Journal of the Acoustical Society of Korea
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    • v.16 no.3E
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    • pp.32-36
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    • 1997
  • This study models mobile communication channels as a discrete finite Markovian process, and Markovian jump linear system having parallel Kalman filter type is applied. What is newly proposed in this paper is an equation for obtaining the transition matrix according to sampling time by using a weighted Gaussian sum approximation and its simple calculation process. Experiments show that the proposed method has superior performance and reuires computation compared to the existing MJLS using the ransition matrix given by a statistical method or from priori information.

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Directional Particle Filter Using Online Threshold Adaptation for Vehicle Tracking

  • Yildirim, Mustafa Eren;Salman, Yucel Batu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.2
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    • pp.710-726
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    • 2018
  • This paper presents an extended particle filter to increase the accuracy and decrease the computation load of vehicle tracking. Particle filter has been the subject of extensive interest in video-based tracking which is capable of solving nonlinear and non-Gaussian problems. However, there still exist problems such as preventing unnecessary particle consumption, reducing the computational burden, and increasing the accuracy. We aim to increase the accuracy without an increase in computation load. In proposed method, we calculate the direction angle of the target vehicle. The angular difference between the direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted, based on their angular difference. Particles with angular difference greater than a threshold is eliminated and the remaining are stored with greater weights in order to increase their probability for state estimation. Threshold value is very critical for performance. Thus, instead of having a constant threshold value, proposed algorithm updates it online. The first advantage of our algorithm is that it prevents the system from failures caused by insufficient amount of particles. Second advantage is to reduce the risk of using unnecessary number of particles in tracking which causes computation load. Proposed algorithm is compared against camshift, direction-based particle filter and condensation algorithms. Results show that the proposed algorithm outperforms the other methods in terms of accuracy, tracking duration and particle consumption.

Implementation of Real-Time Post-Processing for High-Quality Stereo Vision

  • Choi, Seungmin;Jeong, Jae-Chan;Chang, Jiho;Shin, Hochul;Lim, Eul-Gyoon;Cho, Jae Il;Hwang, Daehwan
    • ETRI Journal
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    • v.37 no.4
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    • pp.752-765
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    • 2015
  • We propose a novel post-processing algorithm and its very-large-scale integration architecture that simultaneously uses the passive and active stereo vision information to improve the reliability of the three-dimensional disparity in a hybrid stereo vision system. The proposed architecture consists of four steps - left-right consistency checking, semi-2D hole filling, a tiny adaptive variance checking, and a 2D weighted median filter. The experimental results show that the error rate of the proposed algorithm (5.77%) is less than that of a raw disparity (10.12%) for a real-world camera image having a $1,280{\times}720$ resolution and maximum disparity of 256. Moreover, for the famous Middlebury stereo image sets, the proposed algorithm's error rate (8.30%) is also less than that of the raw disparity (13.7%). The proposed architecture is implemented on a single commercial field-programmable gate array using only 13.01% of slice resources, which achieves a rate of 60 fps for $1,280{\times}720$ stereo images with a disparity range of 256.

A Study on Image Restoration for Removing Mixed Noise while Considering Edge Information (에지정보를 고려한 복합잡음 제거를 위한 영상복원에 관한 연구)

  • Gao, Yinyu;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.10
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    • pp.2239-2246
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    • 2011
  • In image signal processing, image signal is corrupted by various noises and caused the degradation phenomenon. And Images often corrupted by AWGN(additive white gaussian noise) and impulse noise which called mixed noise. In this paper, the algorithm is proposed to remove mixed noise while keeping edge information. The proposed algorithm first classifies the noise type, if the classify result is AWGN, then the mean of the output after using self-adaptive weighted mean filter and median value will be the outfiltering value. And if the noise type is impulse noise, then the noise is removed by a modified nonlinear filter. Also we compare existing methods through the simulation and using PSNR(peak signal to noise ratio) as the standard of judgement of improvement effect. The result of computer simulation on test images indicates that the proposed method is superior to traditional filtering algorithms.

A Study on Denoising for Impulse and Gaussian Noise Images in Digital Images (임펄스 및 가우시안 잡음영상에서 잡음제거에 관한 연구)

  • Long, Xu;Hwang, Yeong-Yeun;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.10a
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    • pp.779-781
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    • 2013
  • As the demand for various multimedia service increases the technology that utilizes image as information transfer method develops rapidly. Though average filter, median filter and weight filter etc. have been proposed to remove various noises that are added to images, the existing methods are short of noise removal and edge reservation performance. Therefore, in this paper an algorithm, in which noise is decided at the first hand, and then it is processed through modified median filter and adaptive weighted average filter, is proposed to effectively remove the complex noise that has been added to an image. And it was compared with existing methods through simulation and PSNR(peak signal to noise ratio) has been used as a criterion.

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Improvement of LMS Algorithm Convergence Speed with Updating Adaptive Weight in Data-Recycling Scheme (데이터-재순환 구조에서 적응 가중치 갱신을 통한 LMS 알고리즘 수렴 속 도 개선)

  • Kim, Gwang-Jun;Jang, Hyok;Suk, Kyung-Hyu;Na, Sang-Dong
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.9 no.4
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    • pp.11-22
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    • 1999
  • Least-mean-square(LMS) adaptive filters have proven to be extremely useful in a number of signal processing tasks. However LMS adaptive filter suffer from a slow rate of convergence for a given steady-state mean square error as compared to the behavior of recursive least squares adaptive filter. In this paper an efficient signal interference control technique is introduced to improve the convergence speed of LMS algorithm with tap weighted vectors updating which were controled by reusing data which was abandoned data in the Adaptive transversal filter in the scheme with data recycling buffers. The computer simulation show that the character of convergence and the value of MSE of proposed algorithm are faster and lower than the existing LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data buffer without complexity of computation. Adaptive transversal filter with proposed data recycling buffer algorithm could efficiently reject ISI of channel and increase speed of convergence in avoidance burden of computational complexity in reality when it was experimented having the same condition of LMS algorithm.