• Title/Summary/Keyword: Adaptive performance

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A sturdy on centralized adaptive control of robot manipulator (로봇 매니플레이터의 집중 적응 제어에 관한 연구)

  • 박성기;홍규장;이상철;정찬수
    • 제어로봇시스템학회:학술대회논문집
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    • 1988.10a
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    • pp.45-49
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    • 1988
  • This paper presents a centralized adaptive control scheme based on perturbation equations in the vicinity of a desired trajectory,which are used to design a feedback control about the desired trajectory. This adaptive control scheme reduces the manipulator control problem from a nonlinear control to controlling a linear control system about a desried trajectory. Computer simulation studies of a two-joint manipulator are performed on a IBM-PC to illustrate the performance of this adaptive control scheme.

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Performance of Adaptive Modulation and Coding with Transmit Diversity in Rayleigh fading Channel (레일리 페이딩 채널에서 전송 안테나 다이버시티 기법을 적용한 Adaptive Modulation and Coding의 성능 분석)

  • 김인경;김주응;강창언;홍대식
    • Proceedings of the IEEK Conference
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    • 2001.06a
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    • pp.73-76
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    • 2001
  • A key requirement for packet based wireless communication systems is to provide a high data rate packet service and improved throughput. To achieve a high throughput, adaptive methods for adjustment of the modulation and coding can be used. In this paper, we propose and analyze a scheme which is a combination of an adaptive modulation and coding(AMC) and transmit diversity(TD). Two different TD schemes are analysed: STTD and STD. Proposed system provides significant improvement in the average throughput.

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A Study on Fast Wavelet Based Adaptive Algorithm for Improvement of Hearing Aids (디지털보청기 시스템의 성능향상을 위한 고속 웨이브렛 기반 적응알고리즘에 관한 연구)

  • 오신범;이채욱;박세기;강명수
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.2459-2462
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    • 2003
  • In this paper, we Propose a wavelet based adaptive algorithm which improves the convergence speed and reduces computational complexity using the fast running FIR filtering efficiently. We compared the performance of the proposed algorithm with time and frequence domain adaptive algorithm using computer simulation of adaptive noise canceler based on synthesis speech.

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Properties of Adaptive Filter Using Hadamard Transformation (하다마드 변환을 이용한 적응필터의 특성)

  • 이태훈;박진배
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.242-242
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    • 2000
  • Comparing to the conventional adaptive filters using LMS algorithm, the proposed adaptive filters can reduce the amounts of computation and have robustness to variance of characteristics of input signals. LMS algorithm is performed in the domain of Hadamard transform after a reference signal and input signal are transformed by fast Hadamard transformation. As a transformation from time domain to Hadamard transformed domain, the proposed filter not only maintains the performance of estimating an input signal but also greatly reduces the number of multiplication. Moreover, the effect of characteristic changes of input signal is decreased. Computer simulation shows the stability and robustness of the proposed filter.

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Adaptive Despreading Receiver for Multi-Code PW-CDMA System with Binary-Level Clipping (이진 레벨 클리핑 multi-code PW-CDMA 시스템을 위한 적응역확산수신기)

  • 최정민;이재홍
    • Proceedings of the IEEK Conference
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    • 2002.06a
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    • pp.13-16
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    • 2002
  • In this paper, we propose adaptive despreading receiver for multi-code PW-CDMA system with binary-level clipping. The distortion due to clipping the multi-level signal causes the performance degradation. Adaptive despreading alleviates the effect of clipping. It is shown that the proposed adaptive despreading receiver achieves smaller BER than conventional despreading receiver for multi-code PW-CDMA system with binary-level clipping.

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Deterministic Disturbance Rejection for Model Reference Adaptive Control (결정론적 외란에 대한 적응제어 알고리즘의 연구)

  • Kim, Yong-Sei;Feng, G.;Lee, Kwon-S.
    • Proceedings of the KIEE Conference
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    • 1993.07a
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    • pp.341-344
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    • 1993
  • This paper presents the general MRAC algorithm design, it's real time implementation and investigates the effect of purely deterministic disturbances to adaptive control algorithm. The design of adaptive control algorithm to reject the disturbances properly is also presented. In real time application, adaptive control algorithm is considered to investigate its performance by using DC motor. Disturbance rejection algorithm is investigated in simulation.

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An Inquiry into Prediction of Learner's Academic Performance through Learner Characteristics and Recommended Items with AI Tutors in Adaptive Learning (적응형 온라인 학습환경에서 학습자 특성 및 AI튜터 추천문항 학습활동의 학업성취도 예측력 탐색)

  • Choi, Minseon;Chung, Jaesam
    • Journal of Information Technology Services
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    • v.20 no.4
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    • pp.129-140
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    • 2021
  • Recently, interest in AI tutors is rising as a way to bridge the educational gap in school settings. However, research confirming the effectiveness of AI tutors is lacking. The purpose of this study is to explore how effective learner characteristics and recommended item learning activities are in predicting learner's academic performance in an adaptive online learning environment. This study proposed the hypothesis that learner characteristics (prior knowledge, midterm evaluation) and recommended item learning activities (learning time, correct answer check, incorrect answer correction, satisfaction, correct answer rate) predict academic achievement. In order to verify the hypothesis, the data of 362 learners were analyzed by collecting data from the learning management system (LMS) from the perspective of learning analytics. For data analysis, regression analysis was performed using the regsubset function provided by the leaps package of the R program. The results of analyses showed that prior knowledge, midterm evaluation, correct answer confirmation, incorrect answer correction, and satisfaction had a positive effect on academic performance, but learning time had a negative effect on academic performance. On the other hand, the percentage of correct answers did not have a significant effect on academic performance. The results of this study suggest that recommended item learning activities, which mean behavioral indicators of interaction with AI tutors, are important in the learning process stage to increase academic performance in an adaptive online learning environment.

A Performance Comparison of DSE-MMA and DQE-MMA Adaptive Equalization Algorithm using Dither Signal (Dither 신호를 이용한 DSE-MMA와 DQE-MMA 적응 등화 알고리즘의 성능 비교)

  • Lim, Seung-Gag;You, Jeong-Bong;Kang, Dae-Soo
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.1
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    • pp.45-50
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    • 2022
  • This paper compares the equalization performance of the DSE-MMA (Dithered Signed Error-MMA) and DQE-MMA (Dithered Quantized Error-MMA) adaptive equalization algorithm based on the dither signal in order to reduce the intersymbol interference occurs at communication channel. These algorithm was emerged in ordr to reduction of arithmetic operation than current MMA, it makes the independent and identical distribute the quantized error component by performing the 1 or N bit quautizer after adding the dither singal in obtaining the error signal for adapting process. It is possible to improve the robustness performance of adaptive algorithm, but degrade the MSE performance in steady state by dither signal. The paper directly compare the DSE-MMA and DQE-MMA adaptive equalization performance of the same concept of dithering in the same communication channel and signal to noise ratio by computer simulation. As a result of simulation, the DQE-MMA has more better in the every performance index, equalizer output constellation, residual isi, MSE and SER performance, but not in convergence speed.

Preliminary Test of Adaptive Neuro-Fuzzy Inference System Controller for Spacecraft Attitude Control

  • Kim, Sung-Woo;Park, Sang-Young;Park, Chan-Deok
    • Journal of Astronomy and Space Sciences
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    • v.29 no.4
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    • pp.389-395
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    • 2012
  • The problem of spacecraft attitude control is solved using an adaptive neuro-fuzzy inference system (ANFIS). An ANFIS produces a control signal for one of the three axes of a spacecraft's body frame, so in total three ANFISs are constructed for 3-axis attitude control. The fuzzy inference system of the ANFIS is initialized using a subtractive clustering method. The ANFIS is trained by a hybrid learning algorithm using the data obtained from attitude control simulations using state-dependent Riccati equation controller. The training data set for each axis is composed of state errors for 3 axes (roll, pitch, and yaw) and a control signal for one of the 3 axes. The stability region of the ANFIS controller is estimated numerically based on Lyapunov stability theory using a numerical method to calculate Jacobian matrix. To measure the performance of the ANFIS controller, root mean square error and correlation factor are used as performance indicators. The performance is tested on two ANFIS controllers trained in different conditions. The test results show that the performance indicators are proper in the sense that the ANFIS controller with the larger stability region provides better performance according to the performance indicators.

Plagiarism Detection among Source Codes using Adaptive Methods

  • Lee, Yun-Jung;Lim, Jin-Su;Ji, Jeong-Hoon;Cho, Hwaun-Gue;Woo, Gyun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.6
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    • pp.1627-1648
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    • 2012
  • We propose an adaptive method for detecting plagiarized pairs from a large set of source code. This method is adaptive in that it uses an adaptive algorithm and it provides an adaptive threshold for determining plagiarism. Conventional algorithms are based on greedy string tiling or on local alignments of two code strings. However, most of them are not adaptive; they do not consider the characteristics of the program set, thereby causing a problem for a program set in which all the programs are inherently similar. We propose adaptive local alignment-a variant of local alignment that uses an adaptive similarity matrix. Each entry of this matrix is the logarithm of the probabilities of the keywords based on their frequency in a given program set. We also propose an adaptive threshold based on the local outlier factor (LOF), which represents the likelihood of an entity being an outlier. Experimental results indicate that our method is more sensitive than JPlag, which uses greedy string tiling for detecting plagiarism-suspected code pairs. Further, the adaptive threshold based on the LOF is shown to be effective, and the detection performance shows high sensitivity with negligible loss of specificity, compared with that using a fixed threshold.