• 제목/요약/키워드: Signal estimate

검색결과 1,284건 처리시간 0.032초

온라인 서포트벡터기계를 이용한 온라인 비정상 사건 탐지 (Online abnormal events detection with online support vector machine)

  • 박혜정
    • Journal of the Korean Data and Information Science Society
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    • 제22권2호
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    • pp.197-206
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    • 2011
  • 신호처리 관련 응용문제에서는 신호에서 실시간으로 발생하는 비정상적인 사건들을 탐지하는 것이 매우 중요하다. 이전에 알려져 있는 비정상 사건 탐지방법들은 신호에 대한 명확한 통계적인 모형을 가정하고, 비정상적인 신호들은 통계적인 모형의 가정 하에서 비정상적인 사건들로 해석한다. 탐지방법으로 최대우도와 베이즈 추정 이론이 많이 사용되고 있다. 그러나 앞에서 언급한 방법으로는 로버스트 하고 다루기 쉬운 모형을 추정한다는 것은 쉽지가 않다. 좀 더 로버스트한 모형을 추정할 수 있는 방법이 필요하다. 본 논문에서는 로버스트 하다고 알려져 있는 서포트 벡터 기계를 이용하여 온라인으로 비정상적인 신호를 탐지하는 방법을 제안한다.

An Artificial Neural Network for Biomass Estimation from Automatic pH Control Signal

  • Hur, Won;Chung, Yoon-Keun
    • Biotechnology and Bioprocess Engineering:BBE
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    • 제11권4호
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    • pp.351-356
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    • 2006
  • This study developed an artificial neural network (ANN) to estimate the growth of microorganisms during a fermentation process. The ANN relies solely on the cumulative consumption of alkali and the buffer capacity, which were measured on-line from the on/off control signal and pH values through automatic pH control. The two input variables were monitored on-line from a series of different batch cultivations and used to train the ANN to estimate biomass. The ANN was refined by optimizing the network structure and by adopting various algorithms for its training. The software estimator successfully generated growth profiles that showed good agreement with the measured biomass of separate batch cultures carried out between at 25 and $35^{\circ}C$.

영상의 잡음 감소를 위한 적응 RLR L-필터 (An Adaptive RLR L-Filter for Noise Reduction in Images)

  • 김수용;배성호
    • 한국멀티미디어학회논문지
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    • 제12권1호
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    • pp.26-30
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    • 2009
  • 본 논문에서는 로버스트 통계학의 순위 추정을 기반으로 하고 순서통계학의 L-추정자를 이용한 적응 순환 최소 순위(RLR) L-필터를 제안한다. 제안한 RLR-L 필터는 비선형 적응알고리즘을 가진 비선형 적응 필터로서 오차의 분산측정을 최소화하는 관점의 최적 필터로 가변적인 스텝 크기를 가지며 적응한다. 제안한 필터는 영상신호와 같은 비정체 신호나 가우시안 잡음 또는 임펄스 잡음과 같은 비선형 채널에 적합하다.

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VALIDITY OF NDVI-BASED BIOPHYSICAL PARAMETERS FOR ECOSYSTEM MODELS

  • Lee, Kyu-Sung;Jang, Ki-Chang;Kim, Tae-Geun;Lee, Seung-Ho;Cho, Hyun-Guk
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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    • pp.543-546
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    • 2006
  • NDVI has been very frequently used to estimate several biophysical parameters that are required for ecosystem models. Leaf area index (LAI), canopy closure, and biomass are among those biophysical parameters that are estimated by empirical relationship with NDVI. However, the type of remote sensing signals (raw DN value, at-sensor radiance, atmospherically corrected reflectance) used can vary the calculation of NDVI. In this study, we tried to attempt to compare the influence of NDVI linked with forest LAI for the watershed-scale ecosystem models to estimate evapotranspiration. Landsat ETM+ data were used to obtain various NDVI values over the study area in central Korea. The NDVI-based LAI and the resultant evapotranspiration estimation were greatly varied by the remote sensing signal applied.

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양자진화 알고리즘을 이용한 얕은 아치의 파라미터 추정 (Parameter Estimation of Shallow Arch Using Quantum-Inspired Evolution Algorithm)

  • 손수덕;하준홍
    • 한국공간구조학회논문집
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    • 제20권1호
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    • pp.95-102
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    • 2020
  • The structural design of arch roofs or bridges requires the analysis of their unstable behaviors depending on certain parameters defined in the arch shape. Their maintenance should estimate the parameters from observed data. However, since the critical parameters exist in the equilibrium paths of the arch, and a small change in such the parameters causes a significant change in their behaviors. Thus, estimation to find the critical ones should be carried out using a global search algorithm. In this paper we study the parameter estimation for a shallow arch by a quantum-inspired evolution algorithm. A cost functional to estimate the system parameters included in the arch consists of the difference between the observed signal and the estimated signal of the arch system. The design variables are shape, external load and damping constant in the arch system. We provide theoretical and numerical examples for estimation of the parameters from both contaminated data and pure data.

Preliminary study of time-of-flight measurement for 3D position sensing system based on acoustic signals

  • Kim, Heung-Gi;Park, Youngjin
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2002년도 ICCAS
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    • pp.79.4-79
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    • 2002
  • Our goal is the development of a system that estimates the location of interested point in a room with accuracy and low cost. Non-contacting position estimating method is widely used in various areas. Among these methods, acoustic signal-based method is the cheapest and provides reasonably accurate estimation as a result of many research efforts. Most of the acoustic-signal-based three-dimensional location estimators such as 3D sonic digitizer are using the ultrasound, and are organized with two procedures; time-of-flight (TOF) estimation and localization estimation. Since the errors in estimating the TOF could be accumulated with that of localization estimate, accuracy of TOF estimate is as...

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Noisy Speech Recognition Based on Noise-Adapted HMMs Using Speech Feature Compensation

  • Chung, Yong-Joo
    • 융합신호처리학회논문지
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    • 제15권2호
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    • pp.37-41
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    • 2014
  • The vector Taylor series (VTS) based method usually employs clean speech Hidden Markov Models (HMMs) when compensating speech feature vectors or adapting the parameters of trained HMMs. It is well-known that noisy speech HMMs trained by the Multi-condition TRaining (MTR) and the Multi-Model-based Speech Recognition framework (MMSR) method perform better than the clean speech HMM in noisy speech recognition. In this paper, we propose a method to use the noise-adapted HMMs in the VTS-based speech feature compensation method. We derived a novel mathematical relation between the train and the test noisy speech feature vector in the log-spectrum domain and the VTS is used to estimate the statistics of the test noisy speech. An iterative EM algorithm is used to estimate train noisy speech from the test noisy speech along with noise parameters. The proposed method was applied to the noise-adapted HMMs trained by the MTR and MMSR and could reduce the relative word error rate significantly in the noisy speech recognition experiments on the Aurora 2 database.

심자도 신호를 이용한 전류원 재구성 (Source Current Reconstruction Based on MCG Signal)

  • 권혁찬;이용호;김진목
    • Progress in Superconductivity
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    • 제4권1호
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    • pp.48-52
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    • 2002
  • When applying a SQUID system for diagnosing heart disease, it is informative to obtain the source current distributions from the measured MCG (magnetocardiogram) signals since the bioelectric activity in the heart is generally represented by distributed current sources. In order to estimate the Primary current distribution in a heart, the minimum norm estimate was computed, assuming a source plane below the chest surface. In the simulation, current distributions, which were computed for the test dipoles represented well the essential feature of the test-current configurations. Source current reconstruction was performed for MCG signal of a healthy volunteer, which was recorded using a 40-channel SQUID system in a magnetically shielded room. It was found that the obtained current distribution is consistent with the electrical activity in a heart.

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PC-기반의 심박변동 팍워스픽트럼밀도 분석기 설계 (The Design of PC-based Power Spectral Density Analyzer of Heart Rate Variability)

  • 김낙환;이응혁;민홍기;홍승홍
    • 대한전기학회논문지:시스템및제어부문D
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    • 제52권9호
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    • pp.547-553
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    • 2003
  • In this paper, we designed the PC-based analyzer of the power spectral density that could estimate the heart rate variability from time series data of R-R interval. The power spectral density estimated that it applied the autoregressive model to the measured electrocardiogram during a short period. Also, the characteristics of the designed analyzer are that it could process of the signal filtering, the generation and recomposition of time series and the feature extraction at the same time. Especially the analyzer reconstructed which applied the lowpass filter of the time series composed by the linear interpolation so as to enhance the signal-to-noise feature. We could estimate the power spectral density that confirmed a variety of power peak with low frequency range and high frequency rang of autonomic nerve by the heart rate variability.

BLE기반 비콘을 이용한 실내 환경에서의 사용자 위치추정 (Estimation of Human Location in Indoor Environment using BLE-based Beacon)

  • 임수종;성민관;윤상석
    • 대한임베디드공학회논문지
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    • 제16권5호
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    • pp.195-200
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    • 2021
  • In this paper, we propose a method for a mobile robot to estimate a specific location of a service provision target using a beacon-tag for the purpose of providing location-based services (LBS) to users in an indoor environment. To estimate the location, the irregular characteristics and error factors of the received signal strength indicator (RSSI) generated from the beacon are analyzed, and the distance conversion function is derived from the RSSI data extracted by applying a Gaussian filter. Then, the distance data converted from the plurality of beacons estimates an indoor location through a triangulation technique. After that, the improvement in the location estimation is analyzed by applying the temporal confidence reasoning technique. The possibility of providing a LBS of a mobile robot was confirmed through a location estimation experiment for a plurality of designated locations in an indoor environment.