• 제목/요약/키워드: Sampling Algorithm

검색결과 1,010건 처리시간 0.03초

컴퓨터 하드 디스크의 정밀 서보 제어 (Precision servo control of a computer hard disk)

  • 전도영
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.286-289
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    • 1996
  • Two servo control algorithms are suggested to reduce the tracking error of a computer hard disk drive. One is the repetitive control to reduce the repeatable tracking error which is not explicitly taken into account in the design of a conventional controller. This algorithm was successfully applied to a commercial disk using a fixed point DSP. The other is the multi-rate sampling control which generates the control output between each sampling times since the sampling time of hard disk drives is limited. These algorithms were shown effectively to reduce tracking errors.

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Scheduling algirithm of data sampling times in the real-time distributed control systems

  • Hong, Seung-Ho
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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    • pp.112-117
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    • 1992
  • The Real-time Distributed Control Systems(RDCS) consist of several distributed control processes which share a network medium to exchange their data. Performance of feedback control loops in the RDCS is subject to the network-induced delays from sensor to controller and from controller to actuator. The network-induced delays are directly dependent upon the data sampling times of the control components which share a network medium. In this study, a scheduling algorithm of determining data sampling times is developed using the window concept, where the sampling data from the control components dynamically share a limited number of windows.

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Particle Swarm Optimization Using Adaptive Boundary Correction for Human Activity Recognition

  • Kwon, Yongjin;Heo, Seonguk;Kang, Kyuchang;Bae, Changseok
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제8권6호
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    • pp.2070-2086
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    • 2014
  • As a kind of personal lifelog data, activity data have been considered as one of the most compelling information to understand the user's habits and to calibrate diagnoses. In this paper, we proposed a robust algorithm to sampling rates for human activity recognition, which identifies a user's activity using accelerations from a triaxial accelerometer in a smartphone. Although a high sampling rate is required for high accuracy, it is not desirable for actual smartphone usage, battery consumption, or storage occupancy. Activity recognitions with well-known algorithms, including MLP, C4.5, or SVM, suffer from a loss of accuracy when a sampling rate of accelerometers decreases. Thus, we start from particle swarm optimization (PSO), which has relatively better tolerance to declines in sampling rates, and we propose PSO with an adaptive boundary correction (ABC) approach. PSO with ABC is tolerant of various sampling rate in that it identifies all data by adjusting the classification boundaries of each activity. The experimental results show that PSO with ABC has better tolerance to changes of sampling rates of an accelerometer than PSO without ABC and other methods. In particular, PSO with ABC is 6%, 25%, and 35% better than PSO without ABC for sitting, standing, and walking, respectively, at a sampling period of 32 seconds. PSO with ABC is the only algorithm that guarantees at least 80% accuracy for every activity at a sampling period of smaller than or equal to 8 seconds.

도플러 레이더 정보를 이용한 샘플링 시점 기반의 생체 신호 측정 알고리즘 개발 (Algorithm Development of Human Body Bio-Signal Measurement based on Sampling Time using Doppler Radar Information)

  • 유재춘;이명의
    • 한국항행학회논문지
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    • 제24권4호
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    • pp.322-327
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    • 2020
  • 최근 도플러 레이더를 이용하여 생체 신호를 획득하는 연구가 개발되어 병상의 환자들에게 적용되는 기술로 사용되고 있다. 하지만 측정되는 맥박의 경우 호흡 신호가 잡음으로 발생하여 정확도가 낮아지는 문제가 발생한다. 본 논문에서는 도플러 레이더를 이용하여 생체신호를 측정할 때 맥박을 측정하기 위한 신호의 정확도를 향상시키기 위한 샘플링 시점 기반의 생체 신호 측정 알고리즘을 제안한다. 제안하는 알고리즘은 두 개의 샘플링 시점을 기반으로 생체 신호 측정 시 발생되는 잡음을 제거하여 측정 생체 신호의 정확도를 높이는 것으로 실제 의료 장비 및 기존 생체 신호 알고리즘과 비교하였을 때, 의료 장비와 90% 이상의 유사함을 보이며, 또한 기존 알고리즘에 비해 심한 진폭의 변화가 최소화 된 것을 확인하였다.

Stochastically Dependent Sequential Acceptance Sampling Plans

  • Kim, Won-Kyung
    • 품질경영학회지
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    • 제25권3호
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    • pp.22-38
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    • 1997
  • In a traditional sequential acceptance sampling plan, it is assumed that the sampled items are independent each other. In this paper, stochastically dependent sequential acceptance sampling plans are dealt when there exists dependency between sampled items. Monte-Calro algorithm is used to find the acceptance and rejection probabilities of a lot. The number of defectives for the test to be accepted and rejected in probability ratio sequential test can be found by using these probabilities. The formula for measures of performance of these sampling plans is developed. Type I and II error probabilities are estimated by simulation. This research can be a, pp.ied to sequential sampling procedures in place of control charts where there is a recognized and necessary dependency during the production processes. Also, dependent multiple acceptance sampling plans can be derived by extending this sequential sampling procedure. As a numerical example, a Markov dependent process model is given, and the characteristics of the sampling plans are examined according to the change of the dependency factor.

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하이브리드 업샘플링을 이용한 베이시안 초해상도 영상처리 (Super-Resolution Image Processing Algorithm Using Hybrid Up-sampling)

  • 박종현;강문기
    • 전기학회논문지
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    • 제57권2호
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    • pp.294-302
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    • 2008
  • In this paper, we present a new image up-sampling method which registers low resolution images to the high resolution grid when Bayesian super-resolution image processing is performed. The proposed up-sampling method interpolates high-resolution pixels using high-frequency data lying in all the low resolution images, instead of up-sampling each low resolution image separately. The interpolation is based on B-spline non-uniform re-sampling, adjusted for the super-resolution image processing. The experimental results demonstrate the effects when different up-sampling methods generally used such as zero-padding or bilinear interpolation are applied to the super-resolution image reconstruction. Then, we show that the proposed hybird up-sampling method generates high-resolution images more accurately than conventional methods with quantitative and qualitative assess measures.

A Cost Effective Reference Data Sampling Algorithm Using Fractal Analysis

  • Lee, Byoung-Kil;Eo, Yang-Dam;Jeong, Jae-Joon;Kim, Yong-Il
    • ETRI Journal
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    • 제23권3호
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    • pp.129-137
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    • 2001
  • A random sampling or systematic sampling method is commonly used to assess the accuracy of classification results. In remote sensing, with these sampling methods, much time and tedious work are required to acquire sufficient ground truth data. So, a more effective sampling method that can represent the characteristics of the population is required. In this study, fractal analysis is adopted as an index for reference sampling. The fractal dimensions of the whole study area and the sub-regions are calculated to select sub-regions that have the most similar dimensionality to that of the whole area. Then the whole area's classification accuracy is compared with those of sub-regions, and it is verified that the accuracies of selected sub-regions are similar to that of whole area. A new kind of reference sampling method using the above procedure is proposed. The results show that it is possible to reduce sampling area and sample size, while keeping the same level of accuracy as the existing methods.

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저비율 샘플링 음향 센서네트워크에서 DTW-Cosine 알고리즘을 이용한 목표물 식별기법 (Target Classification in Sparse Sampling Acoustic Sensor Networks using DTW-Cosine Algorithm)

  • 김영수;강종구;김대영
    • 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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    • 제14권2호
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    • pp.221-225
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    • 2008
  • 센서네트워크에서 목표물 탐지하는데 있어 높은 샘플링이 수반되어야 하는 주파수 분석을 피하기 위하여, 낮은 샘플링 데이타를 이용하더라도 목표물 식별이 가능한 시계열(Time-series) 분석 기법으로서 시간 정합 유사도 측정 알고리즘을 소개하고 그 중에 가장 우수한 DTW-Cosine 알고리즘을 제안한다. 시계열 분석 기법을 이용하여 패턴을 비교하기 위해서는 지역 시간 이동 문제와 공간 신호 변이 문제를 극복해야 하는데 DTW-Cosine 알고리즘은 이를 효과적으로 극복함과 동시에 Smoothing 기법을 통하여 다른 시간 정합 유사도 측정 알고리즘들에 비해 전체적으로 최소 10.31% 이상의 우수한 성능을 보였다.

수동센서를 이용한 효율적인 표적추적을 위한 적응적 자원관리 알고리듬 연구 (Efficient Target Tracking with Adaptive Resource Management using a Passive Sensor)

  • 김우찬;이해호;안명환;이범직;송택렬
    • 제어로봇시스템학회논문지
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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.

Top-${\kappa}$ 유사도 조인을 위한 샘플링 기반 알고리즘 (A Sampling-based Algorithm for Top-${\kappa}$ Similarity Joins)

  • 박종수
    • 한국정보과학회논문지:데이타베이스
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    • 제41권4호
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    • pp.256-261
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    • 2014
  • Top-${\kappa}$ 유사도 조인 문제는 두 개의 입력 레코드 집합들에서 유사도를 기준한 상위 ${\kappa}$ 개의 레코드 쌍을 찾는 것이다. 샘플링 기법을 이용하여 상위 ${\kappa}$ 개의 유사도 조인 쌍을 반환하는 효율적인 알고리즘을 제안한다. 입력 레코드들의 표본에서 집합 유사도 조인들의 히스토그램을 구성하고, 상위 ${\kappa}$ 개의 조인 쌍을 위한 추정 유사도 한계치를 통계 추론으로 95% 신뢰 구간의 오차 한계 내에서 계산한다. 상위 ${\kappa}$ 개의 유사도 조인을 얻기 위하여 최소-히프 구조를 사용하는 일반 유사도 조인 알고리즘에 이 추정 한계치를 적용한다. 대 용량의 실제 데이터집합에서의 실험결과는 제안된 알고리즘의 좋은 성능을 보여준다.