• Title/Summary/Keyword: Adaptive Smoothing

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Performance Improvement of Polynomial Adaline by Using Dimension Reduction of Independent Variables (독립변수의 차원감소에 의한 Polynomial Adaline의 성능개선)

  • Cho, Yong-Hyun
    • Journal of the Korean Society of Industry Convergence
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    • v.5 no.1
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    • pp.33-38
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    • 2002
  • This paper proposes an efficient method for improving the performance of polynomial adaline using the dimension reduction of independent variables. The adaptive principal component analysis is applied for reducing the dimension by extracting efficiently the features of the given independent variables. It can be solved the problems due to high dimensional input data in the polynomial adaline that the principal component analysis converts input data into set of statistically independent features. The proposed polynomial adaline has been applied to classify the patterns. The simulation results shows that the proposed polynomial adaline has better performances of the classification for test patterns, in comparison with those using the conventional polynomial adaline. Also, it is affected less by the scope of the smoothing factor.

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Adaptive Probabilistic Neural Network for Prediction of Compressive Strength of Concrete (콘크리트 압축강도 추정을 위한 적응적 확률신경망 기법)

  • 김두기;이종재;장성규
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2004.10a
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    • pp.542-549
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    • 2004
  • The compressive strength of concrete is commonly used criterion in producing concrete. However, the tests on the compressive strength are complicated and time-consuming. More importantly, it is too late to make improvement even if the test result does not satisfy the required strength, since the test is usually performed at the 28th day after the placement of concrete at the construction site. Therefore, accurate and realistic strength estimation before the placement of concrete is being highly required. In this study, the estimation of the compressive strength of concrete was performed by probabilistic neural network (PNN) on the basis of concrete mix proportions. The estimation performance of PNN was improved by considering the correlation between input data and targeted output value. Adaptive probabilistic neural network (APNN) was proposed to automatically calculate the smoothing parameter in the conventional PNN by using the scheme of dynamic decay adjustment algorithm. The conventional PNN and APNN were applied to predict the compressive strength of concrete using actual test data of a concrete company. APNN showed better results than the conventional PNN in predicting the compressive strength of concrete.

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A Study on Individual Tap-Power Estimation for Improvement of Adaptive Equalizer Performance

  • Kim, Nam-Yong
    • Journal of electromagnetic engineering and science
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    • v.4 no.1
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    • pp.23-29
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    • 2004
  • In this paper we analyze convergence constraints and time constant of IT-LMS algorithm and derive a method of making it's time constant independent of signal power by using input variance estimation. The method for estimating the input variance is to use a single-pole low-pass filter(LPF) with common smoothing parameter value, θ. The estimator is with narrow bandwidth for large θ but with wide bandwidth for small θ. This small θ gives long term average estimation(low frequency) of the fluctuating input variance well as short term variations (high frequency) of the input power. In our simulations of multipath communication channel equalization environments, the method with large θ has shown not as much improved convergence speed as the speed of the original IT-LMS algorithm. The proposed method with small θ=0.01 reach its minimum MSE in 100 samples whereas the IT-LMS converges in 200 samples. This shows the proposed, tap-power normalized IT-LMS algorithm can be applied more effectively to digital wireless communication systems.

Identification of guideway errors in the end milling machine using geometric adaptive control algorithm (기하학적 적응제어에 의한 엔드밀링머시인의 안내면 오차 규명)

  • 정성종;이종원
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.12 no.1
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    • pp.163-172
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    • 1988
  • An off-line Geometric Adaptive Control Scheme is applied to the milling machine to identify its guideway errors. In the milling process, the workpiece fixed on the bed travels along the guideway while the tool and spindle system is fixed onto the machine. The scheme is based on the exponential smoothing of post-process measurements of relative machining errors due to the tool, workpiece and bed deflections. The guideway error identification system consists of a gap sensor, a, not necessarily accurate, straightedge, and the numerical control unit. Without a priori knowledge of the variations of the cutting parameters, the time-varying parameters are also estimated by an exponentially weighted recursive least squares method. Experimental results show that the guideway error is well identified within the range of RMS values of geometric error changes between machining passes disregarding the machining conditions.

AUTOMATED ADAPTIVE TETRAHEDRAL ELEMENT GENERATION FOR THREE-DIMENSIONAL METAL FORMING SIMULATION (삼차원 소성가공 공정 시뮬레이션을 위한 지능형 사면체 요소망 자동생성)

  • Lee M. C.;Joun M. S.
    • Proceedings of the Korean Society for Technology of Plasticity Conference
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    • 2005.05a
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    • pp.203-208
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    • 2005
  • In this paper, an automated adaptive mesh generation scheme, based on an advancing-front-Delaunay method, is developed for finite element simulation of three dimensional bulk metal forming processes. During the simulation, the finite element mesh system is adaptively remeshed whenever the mesh is unacceptable. Several schemes are developed such as curvature compensation scheme to minimize volume loss, optimal smoothing scheme to improve element quality, etc. The presented approach is evaluated and applied to automatic forging simulation in order to demonstrate the effect of the developed schemes.

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MRF-based Adaptive Noise Detection Algorithm for Image Restoration (영상 복원을 위한 MRF 기반 적응적 노이즈 탐지 알고리즘)

  • Nguyen, Tuan-Anh;Hong, Min-Cheol
    • Journal of Korea Multimedia Society
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    • v.16 no.12
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    • pp.1368-1375
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    • 2013
  • In this paper, we presents a spatially adaptive noise detection and removal algorithm. Under the assumption that an observed image and the additive noise have Gaussian distribution, the noise parameters are estimated with local statistics, and the parameters are used to define the constraints on the noise detection process, where the first order Markov Random Field (MRF) is used. In addition, an adaptive low-pass filter having a variable window sizes defined by the constraints on noise detection is used to control the degree of smoothness of the reconstructed image. Experimental results demonstrate the capability of the proposed algorithm.

Adaptive Multimedia Synchronization Using Waiting Time (대기시간을 이용한 적응형 멀티미디어 동기화 기법)

  • Lee, Gi-Seong;Lee, Geun-Wang;Lee, Jong-Chan;O, Hae-Seok
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.2S
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    • pp.649-655
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    • 2000
  • Real-time application programs have constraints which need to be met between media-data. These constraints represents the delay time ad quality of service between media-data to be presented. In order to efficiently describe the delay time and quality of service, a new synchronization mechanism is needed. Proposed paper is a dynamic synchronization that minimized the effects of adaptive transmission delay time. That is, the method meets the requirements of synchronization between media-dat by handling dynamically the adaptive waiting time resulted from variations of delay time. In addition, the mechanism has interval adjustment using maximum delay jitter time. This paper decreases the data loss resulted from variation of delay time and from loss time of media-data by means of applying delay jitter in order to deal with synchronization interval adjustment. Plus, the mechanism adaptively manages the waiting time of smoothing buffer, which leads to minimize the gap from the variation of delay time. The proposed paper is suitable to the system which requires the guarantee of high quality of service and mechanism improves quality of services such as decrease of loss rate, increase of playout rate.

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Local Similarity based Document Layout Analysis using Improved ARLSA

  • Kim, Gwangbok;Kim, SooHyung;Na, InSeop
    • International Journal of Contents
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    • v.11 no.2
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    • pp.15-19
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    • 2015
  • In this paper, we propose an efficient document layout analysis algorithm that includes table detection. Typical methods of document layout analysis use the height and gap between words or columns. To correspond to the various styles and sizes of documents, we propose an algorithm that uses the mean value of the distance transform representing thickness and compare with components in the local area. With this algorithm, we combine a table detection algorithm using the same feature as that of the text classifier. Table candidates, separators, and big components are isolated from the image using Connected Component Analysis (CCA) and distance transform. The key idea of text classification is that the characteristics of the text parallel components that have a similar thickness and height. In order to estimate local similarity, we detect a text region using an adaptive searching window size. An improved adaptive run-length smoothing algorithm (ARLSA) was proposed to create the proper boundary of a text zone and non-text zone. Results from experiments on the ICDAR2009 page segmentation competition test set and our dataset demonstrate the superiority of our dataset through f-measure comparison with other algorithms.

A Power-Aware Scheduling Algorithm with Voltage Transition Overhead (전압 변경 오버헤드를 고려한 전력 관리 알고리즘)

  • Kweon, Hyek-Seong;Ahn, Byoung-Chul
    • Journal of Korea Multimedia Society
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    • v.11 no.5
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    • pp.641-650
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    • 2008
  • As portable devices are used widely, power management algorithm is essential to extend battery use time on small-sized battery power. Although many methods have been proposed, they assumed the voltage transition overhead was negligible or was considered partially. However, the voltage transition overhead might not guarantee to schedule real-time tasks in portable multimedia systems. This paper proposes the adaptive power-aware algorithm to minimize the power consumption by considering the voltage transition overhead. It selects only a few discrete frequencies from the whole frequencies of a system and adjusts the interval between two consecutive frequencies based on the system utilization to reduce the number of frequency change. This algorithm saves the power consumption about 10 to 25 percent compared to a CC RT-DVS method and a frequency-smoothing method.

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A Study on Performance Analysis of Smart Antennas for WLAN System in a Multipath Environment (다경로 환경에서 WLAN 시스템을 위한 스마트 안테나의 성능 분석에 관한 연구)

  • Kim Hyun-Woong;Chang Byong-Kun
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.16 no.2 s.93
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    • pp.182-188
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    • 2005
  • This paper presents an efficient technique for interference suppression in IEEE 802.11b WLAN systems. A linearly constrained adaptive array processor which may improve reception performance of WLAN device by reducing co-channel interference signal and multipath effects effectively was proposed. A spatial smoothing method is used to prevent cancellation of a desired signal in a coherent environment and also integral nulling method is employed to improve the array performance in indoor environment. It was shown that the integral nulling approach performed best while the spatial smoothing method performed better than linearly constrained array processing. The performance of the WLAN system may be improved by the proposed methods which reduce co-channel, coherent, and WPAN interferences effectively.