• Title/Summary/Keyword: Transition Probability

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Simulation of a Diffusion Flame in Turbulent Mixing Layer by the Flame Hole Dynamics Model with Level-Set Method (Level-Set 방법이 적용된 Flame Hole Dynamics 모델을 통한 난류 혼합층 확산화염 모사)

  • Kim, Jun-Hong;Chung, S.H.;Ahn, K.Y.;Kim, J.S.
    • 한국연소학회:학술대회논문집
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    • 2004.06a
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    • pp.102-111
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    • 2004
  • Partial quenching structure of turbulent diffusion flames in a turbulent mixing layer is investigated by the method of flame hole dynamics to develope a prediction model for the turbulent lift off. The present study is specifically aimed to remedy the problem of the stiff transition of the conditioned partial burning probability across the crossover condition by adopting level-set method which describes propagating or retreating flame front with specified propagation speed. In light of the level-set simulations with two model problems for the propagation speed, the stabilizing conditions for a turbulent lifted flame are suggested. The flame hole dynamics combined with level-set method yields a temporally evolving turbulent extinction process and its partial quenching characteristics is compared with the results of the previous model employing the flame-hole random walk mapping. The probability to encounter reacting' state, conditioned with scalar dissipation rate, demonstrated that the conditional probability has a rather gradual transition across the crossover scalar dissipation rate in contrast to the stiff transition of resulted from the flame-hole random walk mapping and could be attributed to the finite response of the flame edge propagation.

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Simulation of a Diffusion Flame in Turbulent Mixing Layer by the Flame Hole Dynamics Model with Level-Set Method (Level-Set 방법이 적용된 Flame Hole Dynamics 모델을 통한 난류 혼합층 확산화염의 모사)

  • Kim, Jun-Hong;Chung, S.H.;Ahn, K.Y.;Kim, J.S.
    • Journal of the Korean Society of Combustion
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    • v.9 no.2
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    • pp.18-29
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    • 2004
  • Partial quenching structure of diffusion flames in a turbulent mixing layer has been investigated by the method of flame hole dynamics in oder to develope a prediction model for the phenomenon of turbulent flame lift off. The present study is specifically aimed to remedy the shortcoming of the stiff transition of the conditioned partial burning probability across the crossover condition by employing the level-set method which enables us to include the effect of finite flame edge propagation speed. In light of the level-set simulation results with two models for the edge propagation speed, the stabilizing conditions for turbulent lifted flame are suggested. The flame hole dynamics combined with the level-set method yields a temporally evolving turbulent extinction process and its partial quenching characteristics is compared with the results of the previous model employing the flame-hole random walk mapping based on three critical scalar dissipation rates. The probability to encounter reacting state, conditioned with scalar dissipation rate, demonstrated that the conditional probability has a rather gradual transition across the crossover scalar dissipation rate. Such a smooth transition is attributed to the finite response of the flame edge propagation.

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Performance Analysis of Wireless Communication System with FSMC Model in Nakagami-m Fading Channel (Nakagami-m 페이딩 채널에서 FSMC 모델에 의한 무선 통신시스템의 성능 분석)

  • 조용범;노재성;조성준
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.8 no.5
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    • pp.1010-1019
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    • 2004
  • In this paper, we represent Nakagami-m fading channel as finite-State Markov Channel (FSMC) and analyze the performance of wireless communication system with varying the fading channel condition. In FSMC model, the received signal's SNR is divided into finite intervals and these intervals are formed into Markov chain states. Each state is modeled by a BSC and the transition probability is dependent upon the physical characterization of the channel. The steady state probability and average symbol error rate of each state and transition probability are derived by numerical analysis and FSMC model is formed with these values. We found that various fading channels can be represented with FSMC by changing state transition index. In fast fading environment in which state transition index is large, the channel can be viewed as i.i.d. channel and on the contrary, in slow fading channel where state transition index is small, the channel can be represented by simple FSMC model in which transitions occur between just adjacent states. And we applied the proposed FSMC model to analyze the coding gain of random error correcting code on various fading channels via computer simulation.

The Low Probability of Intercept RADAR Waveform Based on Random Phase and Code Rate Transition for Doppler Tolerance Improvement (도플러 특성 개선을 위한 랜덤 위상 및 부호율 천이 기반 저피탐 레이다 파형)

  • Lee, Ki-Woong;Lee, Woo-Kyung
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.26 no.11
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    • pp.999-1011
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    • 2015
  • In modern electronic warfare, RADAR is under constant threat of ECM(Electronic Counter Measures) signals from nearby jammers. The conventional linear frequency modulated(Linear-FM) waveform is easy to be intercepted to estimate its signal parameters due to its periodical phase transition. Recently, APCN(Advanced Pulse Compression Noise) waveform using random amplitude and phase transition was proposed for LPI(Low probability of Intercept). But random phase code signals such as APCN waveform tend to be sensitive to Doppler frequency shift and result in performance degradation during moving target detection. In this paper, random phase and code rate transition based radar waveform(RPCR) is proposed for Doppler tolerance improvement. Time frequency analysis is carried out through ambiguity analysis to validate the improved Doppler tolerance of RPCR waveform. As a means to measure the vulnerability of the proposed RPCR waveform against LPI, WHT(Wigner-Hough Transform) is adopted to analyze and estimate signal parameters for ECCM(Electronic Counter Counter Measures) application.

Online Probability Density Estimation of Nonstationary Random Signal using Dynamic Bayesian Networks

  • Cho, Hyun-Cheol;Fadali, M. Sami;Lee, Kwon-Soon
    • International Journal of Control, Automation, and Systems
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    • v.6 no.1
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    • pp.109-118
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    • 2008
  • We present two estimators for discrete non-Gaussian and nonstationary probability density estimation based on a dynamic Bayesian network (DBN). The first estimator is for off line computation and consists of a DBN whose transition distribution is represented in terms of kernel functions. The estimator parameters are the weights and shifts of the kernel functions. The parameters are determined through a recursive learning algorithm using maximum likelihood (ML) estimation. The second estimator is a DBN whose parameters form the transition probabilities. We use an asymptotically convergent, recursive, on-line algorithm to update the parameters using observation data. The DBN calculates the state probabilities using the estimated parameters. We provide examples that demonstrate the usefulness and simplicity of the two proposed estimators.

Molecular Dynamics Simulation for Monolayers of Alkyl Thiol Molecules at Air-Solid Interfaces

  • 이송희;김한수
    • Bulletin of the Korean Chemical Society
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    • v.17 no.8
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    • pp.700-706
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    • 1996
  • We present the results of molecular dynamics simulations of monolayers of long-chain alkyl thiol [S(CH2)15CH3] molecules on an air-solid interface using the extended collapsed atom model for the chain-molecule and a gold surface for the solid surface. Several molecular dynamics simulations have been performed on monolayers with areas per molecule ranging from 18.30 to 32.10 Å2/molecule. It is found that there exist three possible transitions: a continuous transition characterized by a change in molecular configuration without change in lattice structure, a sudden transition characterized by the distinct lattice defects and perfect islands, and a third transition characterized by the appearance of a random, liquid-like state. The analysis of probability distributions of the segments shows that the structure of the chain-molecules at the air-solid interface is completely different from that at the air-water interface in the view of the degree of overlap of the probability distributions of the neighbor segments. The calculated diffusion coefficients of the chain-molecules on the monolayers seem to be not directly related to any one of the three transitions. However, the large diffusion of the molecules enhanced by the increment of the area per molecule may induce the second transition.

Automatic Generation of Music Accompaniment Using Reinforcement Learning (강화 학습을 통한 자동 반주 생성)

  • Kim, Na-Ri;Kwon, Ji-Yong;Yoo, Min-Joon;Lee, In-Kwon
    • 한국HCI학회:학술대회논문집
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    • 2008.02a
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    • pp.739-743
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    • 2008
  • In this paper, we introduce a method for automatically generating accompaniment music, according to user's input melody. The initial accompaniment chord is generated by analyzing user's input melody. Then next chords are generated continuously based on markov chain probability table in which transition probabilities of each chord are defined. The probability table is learned according to reinforcement learning mechanism using sample data of existing music. Also during playing accompaniment, the probability table is learned and refined using reward values obtained in each status to improve the behavior of playing the chord in real-time. The similarity between user's input melody and each chord is calculated using pitch class histogram. Using our method, accompaniment chords harmonized with user's melody can be generated automatically in real-time.

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Traffic Analysis of a Cognitive Radio Network Based on the Concept of Medium Access Probability

  • Khan, Risala T.;Islam, Md. Imdadul;Amin, M.R.
    • Journal of Information Processing Systems
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    • v.10 no.4
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    • pp.602-617
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    • 2014
  • The performance of a cognitive radio network (CRN) solely depends on how precisely the secondary users can sense the presence or absence of primary users. The incorporation of a spatial false alarm makes deriving the probability of a correct decision a cumbersome task. Previous literature performed this task for the case of a received signal under a Normal probability density function case. In this paper we enhance the previous work, including the impact of carrier frequency, the gain of antennas on both sides, and antenna heights so as to observe the robustness against noise and interference and to make the correct decision of detection. Three small scale fading channels: Rayleigh, Normal, and Weibull were considered to get the real scenario of a CRN in an urban area. The incorporation of a maximal-ratio combining and selection combing with a variation of the number of received antennas have also been studied in order to achieve the correct decision of spectral sensing, so as to serve the cognitive users. Finally, we applied the above concept to a traffic model of the CRN, which we based on a two-dimensional state transition chain.

Bayesian Conjugate Analysis for Transition Probabilities of Non-Homogeneous Markov Chain: A Survey

  • Sung, Minje
    • Communications for Statistical Applications and Methods
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    • v.21 no.2
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    • pp.135-145
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    • 2014
  • The present study surveys Bayesian modeling structure for inferences about transition probabilities of Markov chain. The motivation of the study came from the data that shows transitional behaviors of emotionally disturbed children undergoing residential treatment program. Dirichlet distribution was used as prior for the multinomial distribution. The analysis with real data was implemented in WinBUGS programming environment. The performance of the model was compared to that of alternative approaches.

Forecasting Probability of Precipitation Using Morkov Logistic Regression Model

  • Park, Jeong-Soo;Kim, Yun-Seon
    • Communications for Statistical Applications and Methods
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    • v.14 no.1
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    • pp.1-9
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    • 2007
  • A three-state Markov logistic regression model is suggested to forecast the probability of tomorrow's precipitation based on the current meteorological situation. The suggested model turns out to be better than Markov regression model in the sense of the mean squared error of forecasting for the rainfall data of Seoul area.