• 제목/요약/키워드: Stochastic prediction

검색결과 217건 처리시간 0.025초

CELP 보코더의 성능 개선 및 실시간 구현 (Performance improvement and Realtime implementation in CELP Coder)

  • 정창경
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 1994년도 제11회 음성통신 및 신호처리 워크샵 논문집 (SCAS 11권 1호)
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    • pp.199-204
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    • 1994
  • In this paper, we researched abut CELP speech coding algorithm using efficlent pseudo-stochastic block codes, adaptive-codebook and improved fixed-gain codebook. The pseudo-stochastic block codes refer to stochastically populated block codes in which the adjacent codewords in an innovation codebook are non-independent. The adaptive-codebook was made with previous prediction speech data by storage-shift register. This CELP coding algorithm enables the coding of toll quality speech at bit rates from 4.8kbits/s to 9.6 kbits/s. This algorithm was realized TMS320C30 microprocessor in realtime.

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大氣汚染濃度에 관한 確率모델 (A Stochastic Model for Air Pollutant Concentration)

  • 김해경
    • 한국대기환경학회지
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    • 제7권2호
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    • pp.127-136
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    • 1991
  • This paper is concerned with the development and application of a stochastic model for daily sulphur dioxide $(SO_2)$ concentrations in urban area (Seoul). For this, the characteristics of the regression trend, periodicity and dependence of the daily $SO_2$ concentration are investigated by a statistisical analysis of the daily average $SO_2$ values measured in Seoul area during 1989 $\sim$ 1990. Based on these, nonlinear regression time series model for the prediction of daily $SO_2$ concentrations is derived. A statistical procedure for using the model to predict the concentration level is also proposed.

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단기 통행시간예측 모형 개발에 관한 연구 (The study of Estimation model for the short-term travel time prediction)

  • 이승재;김범일;권혁
    • 한국ITS학회 논문지
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    • 제3권1호
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    • pp.31-44
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    • 2004
  • 최근 몇 년간 도시교통문제의 해결책으로 부각되어온 지능형교통체계(ITS : Intelligent Transport System)의 한 분야로 첨단여행자 정보체계(ATIS : Advanced Travellers Information System)는 자동차에 장착된 항법장치(CNS)를 통해 운전자에게 원하는 목적지까지 최적경로를 제공하거나 경로에 대한 통행시간 정보를 제공 또는 예측해 주는 시스템이다. 본 연구에서는 이러한 최적경로 제공이나 통행시간 예측에 있어 좀 더 효율적인 통행시간 예측모형을 개발하고자 하였다. 현재까지의 통행시간 예측은 운전자가 통행을 시작할 때의 교통상황에 대한 정보이기 때문에 운전 중에 달라지는 교통상황을 반영할 수 없어 이로 인해 운전자가 경험하는 통행시간과 큰 차이를 발생시킬 수 있다. 본 연구에서는 이러한 불합리적인 예측시스템을 개선시킬 수 있는 예측된(predicted) 통행시간 예측 모형을 개발하고자 하였다. 이를 위해 우선 통행시간 예측모형을 특정링크에 적용시켜 모형들의 예측치와 실제 통행시간을 비교하여 교통량 흐름 패턴에 따라 어느 모형이 적합한지, 또 예측시간이 달라짐에 따라 모형들의 적합도와 첨두와 비첨두시 예측시간 간격에 따라 예측치와 실측치의 오차율을 알아보았다, 이를 통해 선정된 확률과정 모형과 칼만 필터링 예측모형을 서울시의 4개축에 대해서 다시 적용해 보았다. 그 결과 단기통행시간 예측에 있어서는 칼만필터링모형이, 장기 통행시간 예측에 있어서는 확률과정 모형이 통행시간 예측에 있어 우수한 모형임을 밝혀냈다. 마지막으로 서울시 28개 교통축의 5분 후 통행시간 예측에 칼만필터링 모형을 이용하여 오차분석을 적용하여 보았다. 그 결과 칼만필터링 모형이 신뢰할 만한 오차율을 보였다.

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ADAPTIVE CHANDRASEKHAR FILLTER FOR LINEAR DISCRETE-TIME STATIONALY STOCHASTIC SYSTEMS

  • Sugisaka, Masanori
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국제학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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    • pp.1041-1044
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    • 1988
  • This paper considers the design problem of adaptive filters based an the state-space models for linear discrete-time stationary stochastic signal processes. The adaptive state estimator consists of both the predictor and the sequential prediction error estimator. The discrete Chandrasakhar filter developed by author is employed as the predictor and the nonlinear least-squares estimator is used as the sequential prediction error estimator. Two models are presented for calculating the parameter sensitivity functions in the adaptive filter. One is the exact model called the linear innovations model and the other is the simplified model obtained by neglecting the sensitivities of the Chandrasekhar X and Y functions with respect to the unknown parameters in the exact model.

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An iterative hybrid random-interval structural reliability analysis

  • Fang, Yongfeng;Xiong, Jianbin;Tee, Kong Fah
    • Earthquakes and Structures
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    • 제7권6호
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    • pp.1061-1070
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    • 2014
  • An iterative hybrid structural dynamic reliability prediction model has been developed under multiple-time interval loads with and without consideration of stochastic structural strength degradation. Firstly, multiple-time interval loads have been substituted by the equivalent interval load. The equivalent interval load and structural strength are assumed as random variables. For structural reliability problem with random and interval variables, the interval variables can be converted to uniformly distributed random variables. Secondly, structural reliability with interval and stochastic variables is computed iteratively using the first order second moment method according to the stress-strength interference theory. Finally, the proposed method is verified by three examples which show that the method is practicable, rational and gives accurate prediction.

확률 통계적 기법을 이용한 발전설비 고장확률 예측 (Failure Probability Prediction based on probabilistic and stochastic methods in generating units)

  • 이성훈;이승혁;김진오;차승태;김태균
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 추계학술대회 논문집 전력기술부문
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    • pp.69-71
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    • 2004
  • This paper presents a method to predict failure probability related to aging. To calculate failure probability, the Weibull distribution is used due to age-related reliability. The Weibull distribution has shape and scale parameters. Each estimated parameter is obtained from Data Analytic Method (Type II Censoring) which is relatively simpler and faster than the traditional calculation ways for estimating parameters. Also, this paper shows the calculation procedures of a probabilistic failure prediction through a stochastic data analysis. Consequently, the proposed methods would be likely to permit that the new deregulated environment forces utilities to reduce overall costs while maintaining an age-related reliability index.

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품사셋에 의한 운율경계강도의 예측 (Prediction of Prosodic Boundary Strength by means of Three POS(Part of Speech) sets)

  • 엄기완;김진영;김선미;이현복
    • 대한음성학회지:말소리
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    • 제35_36호
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    • pp.145-155
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    • 1998
  • This study intended to determine the most appropriate POS(Part of Speech) sets for predicting prosodic boundary strength efficiently. We used 3-level POB bets which Kim(1997), one of the authors, has devised. Three POS sets differ from each other according to how much grammatical information they have: the first set has maximal syntactic and morphological information which possibly affects prosodic phrasing, and the third set has minimal one. We hand-labelled 150 sentences using each of three POS sets and conducted perception test. Based on the results of the test, stochastic language modeling method was used to predict prosodic boundary strength. The results showed that the use of each POS set led to not too much different efficiency in the prediction, but the second set was a little more efficient than the other two. As far as the complexity in stochastic language modeling is concerned, however, the third set may be also preferable.

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Real-Time Stochastic Optimum Control of Traffic Signals

  • Lee, Hee-Hyol
    • Journal of information and communication convergence engineering
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    • 제11권1호
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    • pp.30-44
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    • 2013
  • Traffic congestion has become a serious problem with the recent exponential increase in the number of vehicles. In urban areas, almost all traffic congestion occurs at intersections. One of the ways to solve this problem is road expansion, but it is difficult to realize in urban areas because of the high cost and long construction period. In such cases, traffic signal control is a reasonable method for reducing traffic jams. In an actual situation, the traffic flow changes randomly and its randomness makes the control of traffic signals difficult. A prediction of traffic jams is, therefore, necessary and effective for reducing traffic jams. In addition, an autonomous distributed (stand-alone) point control of each traffic light individually is better than the wide and/or line control of traffic lights from the perspective of real-time control. This paper describes a stochastic optimum control of crossroads and multi-way traffic signals. First, a stochastic model of traffic flows and traffic jams is constructed by using a Bayesian network. Secondly, the probabilistic distributions of the traffic flows are estimated by using a cellular automaton, and then the probabilistic distributions of traffic jams are predicted. Thirdly, optimum traffic signals of crossroads and multi-way intersection are searched by using a modified particle swarm optimization algorithm to realize real-time traffic control. Finally, simulations are carried out to confirm the effectiveness of the real-time stochastic optimum control of traffic signals.

월유출량계열의 확장과 예측을 위한 추계학적 다중 입출력모형 (Stochastic Multiple Input-Output Model for Extension and Prediction of Monthly Runoff Series)

  • 박상우;전병호
    • 물과 미래
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    • 제28권1호
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    • pp.81-90
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    • 1995
  • 본 연구에서는 장기간의 수문기상자료를 보유하고 있으나 유출량자료의 관측년한이 짧은 유역에서 장기간의 월유출량자료를 확장하고 예측할 수 있는 추계학적 시스템 모형을 개발하고자 한다. 그 방법으로 주기성과 경향성을 갖는 월유출량, 월강수량 및 윌증발량자료를 시계열 분석하여 seasonal ARIMA 형태의 단변량 모형을 유도하는 한편, 각 계열간의 교차상관분석으로부터 월강수량 및 윌증발량을 입력변수로 하고 월유출량을 출력변수로 하는 다중 입력-단일 출력관계의 설명모형을 유도하여 단변량 시계열모형과 비교 검토하였다. 본 연구의 결과 월유출량자료의 확장과 예측에 있어서 다중 입출력모형의 정확성과 적용가능성이 매우 높은 것으로 판단되었다.

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비행하중하에서 2124-T851 알루미늄합금의 피로균열진전 예측 (Prediction of Crack Growth in 2124-7851 Al-Alloy Under Flight-Simulation Loading)

  • 심동석;황돈영;김정규
    • 대한기계학회논문집A
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    • 제26권8호
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    • pp.1487-1494
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    • 2002
  • In this study, to propose the prediction method of the crack growth under flight-simulation loading, crack growth tests are conducted on 2124-7851 aluminum alloy specimens. The prediction of crack growth under flight-simulation loading is performed by the stochastic crack growth model which was developed in previous study. First of all, to reduce the complex load history into a number of constant amplitude events, rainflow counting is applied to the flight-simulation loading wave. The crack growth, then, is predicted by the stochastic crack growth model that can describe the load interaction effect as well as the variability in crack growth process. The material constants required in this model are obtained from crack growth tests under constant amplitude loading and single tensile overload. The curves predicted by the proposed model well describe the crack growth behavior under flight-simulation loading and agree with experimental data. In addition, this model well predicts the variability of fatigue lives.