• Title/Summary/Keyword: convergence of filters

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A Study on an Image Restoration Algorithm in Universal Noise Environments

  • Jin, Bo;Kim, Nam-Ho
    • Journal of information and communication convergence engineering
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    • v.6 no.1
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    • pp.80-85
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    • 2008
  • Images are often corrupted by noises during signal acquisition and transmission. Among those noises, additive white Gaussian noise (AWGN) and impulse noise are most representative. For different types of noise have different characters, how to remove them separately from degraded image is one of the most fundamental problems. Thus, a modified image restoration algorithm is proposed in this paper, which can not only remove impulse noise of random values, but also remove the AWGN selectively. The noise detection step is by calculating the intensity difference and the spatial distance between pixels in a mask. To divide two different noises, the method is based on three weighted parameters. And the weighted parameters in the filtering mask depend on spatial distances, positions of impulse noise and standard deviation of AWGN. We also use the peak signal-to-noise ratio (PSNR) to evaluate restoration performance, and simulation results demonstrate that the proposed method performs better than conventional median-type filters, in preserving edge details.

A Study on the Design of an Adaptive pole Placement Controller with Improved Convergence Properties (개선된 수렴 특성을 갖는 적응 극배치 제어기의 설계에 관한 연구)

  • 홍연찬;김종환
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.41 no.3
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    • pp.311-319
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    • 1992
  • In this paper, a direct adaptive pole placement controller for an unknown linear time-invariant single-input single-output nonminimum phase plant is proposed. To design this direct adaptive pole placement controller, the auxiliary signals are introduced. Consequently, a linear equation error model is formulated for estimating both the controller parameters and the additional auxiliary parameters. To estimate the controller parameters and the additional auxiliary parameters, the exponentially weighted least-squares algorithm is implemented, and a method of selecting the characteristic polynomials of the sensitivity function filters is proposed. In this method, all the past measurement data are weighted exponentially. A series of simulations for a nonminimum phase plant is presented to illustrate some features of both the parameter estimation and the output response of this adaptive pole placement controller.

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Implementation of Image Semantic Segmentation on Android Device using Deep Learning (딥-러닝을 활용한 안드로이드 플랫폼에서의 이미지 시맨틱 분할 구현)

  • Lee, Yong-Hwan;Kim, Youngseop
    • Journal of the Semiconductor & Display Technology
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    • v.19 no.2
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    • pp.88-91
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    • 2020
  • Image segmentation is the task of partitioning an image into multiple sets of pixels based on some characteristics. The objective is to simplify the image into a representation that is more meaningful and easier to analyze. In this paper, we apply deep-learning to pre-train the learning model, and implement an algorithm that performs image segmentation in real time by extracting frames for the stream input from the Android device. Based on the open source of DeepLab-v3+ implemented in Tensorflow, some convolution filters are modified to improve real-time operation on the Android platform.

A Variable Step-Size NLMS Algorithm with Low Complexity

  • Chung, Ik-Joo
    • The Journal of the Acoustical Society of Korea
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    • v.28 no.3E
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    • pp.93-98
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    • 2009
  • In this paper, we propose a new VSS-NLMS algorithm through a simple modification of the conventional NLMS algorithm, which leads to a low complexity algorithm with enhanced performance. The step size of the proposed algorithm becomes smaller as the error signal is getting orthogonal to the input vector. We also show that the proposed algorithm is an approximated normalized version of the KZ-algorithm and requires less computation than the KZ-algorithm. We carried out a performance comparison of the proposed algorithm with the conventional NLMS and other VSS algorithms using an adaptive channel equalization model. It is shown that the proposed algorithm presents good convergence characteristics under both stationary and non-stationary environments despites its low complexity.

An Effective Noise Estimator for Use in Noise Reduction

  • Han, Hag-Yong;Kwon, Ho-Min;Lee, Sung-Mok;Lee, Gi-Dong;Kang, Bong-Soon
    • Journal of information and communication convergence engineering
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    • v.9 no.1
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    • pp.59-63
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    • 2011
  • Conventional noise reduction filtering schemes realize limited improvements of the peak signal-to-noise ratio (PSNR) in the low-level noisy images. The flatness degree and the edge information are effectively used to estimate the noise volume. We propose a noise estimator for reducing noise in the AWGN (additive white gaussian noise) corrupted images using three intermediate image maps (FGM(flatness gray map), FIM(flatness index map), NEM(noise estimate map)). The proposed noise estimator is fed into the conventional noise reduction filters as a pre-processor. The performance of noise reduction is tested in the various AWGN corrupted images.

Machine Learning-Based Filter Parameter Estimation for Inertial/Altitude Sensor Fusion (관성/고도 센서 융합을 위한 기계학습 기반 필터 파라미터 추정)

  • Hyeon-su Hwang;Hyo-jung Kim;Hak-tae Lee;Jong-han Kim
    • Journal of Advanced Navigation Technology
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    • v.27 no.6
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    • pp.884-887
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    • 2023
  • Recently, research has been actively conducted to overcome the limitations of high-priced single sensors and reduce costs through the convergence of low-cost multi-variable sensors. This paper estimates state variables through asynchronous Kalman filters constructed using CVXPY and uses Cvxpylayers to compare and learn state variables estimated from CVXPY with true value data to estimate filter parameters of low-cost sensors fusion.

Adaptive Filter Based PN Code Phase Acquisition Under Frequency Selective Rayleigh Fading Channels

  • Lee, Donghoon;Kim, Jeongchang;Cheun, Kyungwhoon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38A no.5
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    • pp.416-425
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    • 2013
  • A hybrid PN code phase acquisition system based on a least-mean-square adaptive filter, interpreted as a channel estimator is proposed and analyzed for direct-sequence spread-spectrum systems under frequency selective Rayleigh fading channels. Closed form expressions are derived for the filter tap weights and detection/false alarm probabilities. Compared to previously proposed systems, the proposed system achieves smaller mean acquisition times, is more robust to the operating signal-to-noise ratio and allows for multiplication free tap weight updates.

Taps Delayed Lines Architecture Based on Linear Transmit Zero-Forcing Approach for Ultra-Wide Band MIMO Communication Systems

  • Kim, Sang-Choon
    • Journal of information and communication convergence engineering
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    • v.9 no.6
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    • pp.652-656
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    • 2011
  • In this paper, a transmitter-based multipath processing and inter-channel interference (ICI) cancellation scheme for a ultra-wideband (UWB) spatial multiplexing (SM) multiple input multiple output (MIMO) system is presented. It consists of taps delayed lines and zero-forcing (ZF) filters in the transmitter and correlators in the receiver. For a UWB SM MIMO system with N transmit antennas, M receive antennas, and Q resolvable multipath components, the BER performance of a linear transmit ZF scheme is analyzed in a log-normal fading channel and also compared with that of a receiver-based ICI rejection approach. It is found that when M ${\leq}$ N, the transmit ZF processing approach outperforms the ZF receiver while making the mobile units low-cost and low-power.

Linear Robust Target Tracking Filter Using the Range Differences Measured By Formation Flying Multiple UAVs (다중 UAV에서 측정된 거리차 정보를 이용한 선형 강인 표적추적 필터 설계)

  • Lee, Hye-Kyung;Han, Seul-Ki;Ra, Won-Sang
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.61 no.2
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    • pp.284-290
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    • 2012
  • This paper addresses a new passive target tracking problem using the range differences measured by cooperative UAVs. In order to solve the range difference based passive target tracking problem within the framework of linear robust state estimation, the uncertain linear measurement model which contains the stochastic parameter uncertainty is derived by using the noisy range difference measurements. To cope with the performance degradation due to the stochastic parameter uncertainty, the recently developed non-conservative robust Kalman filtering technique [1] is applied. For the cruciform formation flying UAVs, the relationship between the target tracking performance and the measurement errors is quantitatively analyzed. The proposed filter has practical advantages over the classical nonlinear filters because, for its recursive linear structure, it can provide satisfactory convergence properties and is suitable for real-time multiple UAVs applications. Through the simulations, the usefulness of the proposed method is demonstrated.

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

  • Yang, Yoon Gi;Byun, Hee Jung
    • Journal of IKEEE
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    • v.17 no.2
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    • pp.111-118
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    • 2013
  • In this paper, the subband nonlinear adaptive Volterra filters are introduced and its analysis are presented. From the eigenvalue analysis of the input correlation matrix, we show that the proposed subband adaptive Volterra filter has superior convergence performance as compared to the conventional one, which shows that the it can be useful for the recently proposed subband nonlinear adaptive echo canceller. Also, the optimum filter in each subband are introduced and verified from the computer simulations.