• The Journal of the Acoustical Society of Korea
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• 제15권5호
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• pp.30-37
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• 1996

In the communication system, adaptive equalizer using LMS algorithm has slow convergence rate in spite of effectiveness and simplicity. In this paper, we designed the wavelet transform based adaptive equalizer to overcome this problem. The performance of this new approach is compared with that of the time domain LMS algorithm by convergence rate with respect to change of channel distortion and filter order. As a result, the wavelet transform based adaptive equalizer shows the improvements in the speed of convergence compared with LMS algorithm based adaptive equalizer.

• Journal of Broadcast Engineering
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• 제15권5호
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• pp.617-630
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• 2010

At 37th VCEG meeting in Jan. 2009, Toshiba proposed Quadtree-based Adaptive Loop Filter (QALF). The basic concept of QALF is to apply Wiener filter to decoded image after the conventional deblocking filter and to represent the filter on/off flag data for each basic filtering unit in a more efficient way of quadtree structure. QALF could enhance the compression performance of around more than 9%, but the structure of one filter for a decoded frame leaves room for further improvement in the sense that optimal filter for one region of a frame could quite different from the optimal filter for other parts of a picture. This paper proposes multiple adaptive loop filters for better utilization of local characteristics of decoded frame to optimize the region-based Wiener filters. Additional filters, proposed in this paper, cover separate spatial area of each decoded frame according to the performance of previously designed filter(s) to provide the flexibility of rate-distortion based selection of the number of filters.

• Proceedings of the KIEE Conference
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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• pp.2513-2515
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• 2005

Recently genetic algorithm techniques have widely used in adaptive and control schemes for production systems. However, generally it costs a lot of time for leaming in the case applied in control system. Furthermore, the physical meaning of genetic algorithm constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a genetic algorithm used for identification of the process dynamics of Butter-Worth analog filter and it was shown that this method offered superior capability over the genetic algorithm. A genetic algorithm is used to solve the parameter identification problem for linear and nonlinear digital filters. This paper goal estimate Butter-Worth analog filter parameter using the genetic algorithm.

• Journal of Institute of Control, Robotics and Systems
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• 제22권10호
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• pp.797-802
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• 2016

This paper proposes a noble voice recognition method based on an adaptive MFCC and deep learning for embedded systems. To enhance the recognition ratio of the proposed voice recognizer, ambient noise mixed into the voice signal has to be eliminated. However, noise filtering processes, which may damage voice data, diminishes the recognition ratio. In this paper, a filter has been designed for the frequency range within a voice signal, and imposed weights are used to reduce data deterioration. In addition, a deep learning algorithm, which does not require a database in the recognition algorithm, has been adapted for embedded systems, which inherently require small amounts of memory. The experimental results suggest that the proposed deep learning algorithm and HMM voice recognizer, utilizing the proposed adaptive MFCC algorithm, perform better than conventional MFCC algorithms in its recognition ratio within a noisy environment.

• Current Optics and Photonics
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• 제7권4호
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• pp.408-418
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• 2023

Due to the technological limitations of infrared thermography, infrared focal plane array (IFPA) imaging exhibits stripe non-uniformity, which is typically fixed pattern noise that changes over time and temperature on top of existing non-uniformities. This paper proposes a stripe non-uniformity correction algorithm based on scene-adaptive nonlinear filtering. The algorithm first uses a nonlinear filter to remove single-column non-uniformities and calculates the actual residual with respect to the original image. Then, the current residual is obtained by using the predicted residual from the previous frame and the actual residual. Finally, we adaptively calculate the gain and bias coefficients according to global motion parameters to reduce artifacts. Experimental results show that the proposed algorithm protects image edges to a certain extent, converges fast, has high quality, and effectively removes column stripes and non-uniform random noise compared to other adaptive correction algorithms.

• Journal of Institute of Control, Robotics and Systems
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• 제22권7호
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• pp.536-542
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• 2016

To enhance tracking efficiency, a target-tracking filter with a resource management algorithm is required. One of the resource management algorithms chooses or evaluates the proper sampling time using cost functions which are related to the target tracking filter. We propose a resource management algorithm for bearing only tracking environments. Since the tracking performance depends on the system observability, the bearing-only tracking is one of challenging target-tracking fields. The proposed algorithm provides the adaptive sampling time using the variation rate of the error covariance matrix from the target-tracking filter. The simulation verifies the efficiency performance of the proposed algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• 제38권5호
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• pp.556-566
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• 2001

This paper proposes a motion-adaptive de-interlacing algorithm based on EBMF(Edge Based Median Filter) and AMPDF(Adaptive Minimum Pixel Difference Fillet). To compensate 'motion missing'error, which is an important factor in motion-adaptive methods, we used AMPDF which estimates an accurate value using different thresholds after classifying the input image to 4 classes. To efficiently interpolate the moving diagonal edge, we also used EBMF which selects a candidate pixel according to the edge information. Finally, we, to increase the performance, adopted an adaptive interpolation after classifying the input image to moving region, stationary region, and boundary region. Simulation results showed that the proposed method provides better performance than the existing methods.

• The Journal of the Acoustical Society of Korea
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• 제27권2E호
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• pp.64-68
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• 2008

This paper investigates noise reduction performance and performs convergence analysis of a Variable Error Data Normalized Step-Size Least Mean Square(VEDNSS LMS) algorithm. Adopting VEDNSS LMS results in higher system complexity, but noise is reduced providing fast convergence speed Mathematical analysis demonstrates that tap coefficient misadjustment converges. This is confirmed by computer simulation with the proposed algorithm.

• Proceedings of the IEEK Conference
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• 대한전자공학회 2002년도 ITC-CSCC -1
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• pp.678-681
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• 2002

In this paper, we propose a block LMS algorithm using distributed arithmetic (BDA) and a multi-memory block structured BDA (MBDA). Moreover, we propose an effective VLSI architecture of adaptive digital filter using MBDA, and evaluate the sampling rate and output latency.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 한국조명전기설비학회 1992년도 추계학술발표회논문집
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• pp.56-59
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• 1992

Adaptive active attenuation of noise in a duct is considered. A duct is modelled when the acoustic feedback exists. The secondary path transfer function is estimated using multiple model approaches. An IIR structure is assumed for the control filter, and the recursive least mean squares algorithm is used to adjust the filter coefficients.