• Title/Summary/Keyword: Markov transition probability

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Efficient Computations for Evaluating Extended Stochastic Petri Nets using Algebraic Operations

  • Kim, Dong-Sung;Moon, Hong-Ju;Bahk, Je-Hyeong;Kwon, Wook-Hyun;Zygmunt J. Haas
    • International Journal of Control, Automation, and Systems
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    • v.1 no.4
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    • pp.431-443
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    • 2003
  • This paper presents an efficient method to evaluate the performance of an extended stochastic Petri net by simple algebraic operations. The reachability graph is derived from an extended stochastic Petri net, and then converted to a timed stochastic state machine, using a semi-Markov process. The n-th moments of the performance index are derived by algebraic manipulations with each of the n-th moments of transition time and transition probability. For the derivation, three reduction rules are introduced on the transition trajectories in a well-formed regular expression. Efficient computation algorithms are provided to automate the suggested method. The presented method provides a proficient means to derive both the numerical and the symbolic solutions for the performance of an extended stochastic Petri net by simple algebraic manipulations.

Spliced Image Detection Using Characteristic Function Moments of Co-occurrence Matrix (동시 발생 행렬의 특성함수 모멘트를 이용한 접합 영상 검출)

  • Park, Tae-Hee;Moon, Yong-Ho;Eom, Il-Kyu
    • IEMEK Journal of Embedded Systems and Applications
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    • v.10 no.5
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    • pp.265-272
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    • 2015
  • This paper presents an improved feature extraction method to achieve a good performance in the detection of splicing forged images. Strong edges caused by the image splicing destroy the statistical dependencies between parent and child subbands in the wavelet domain. We analyze the co-occurrence probability matrix of parent and child subbands in the wavelet domain, and calculate the statistical moments from two-dimensional characteristic function of the co-occurrence matrix. The extracted features are used as the input of SVM classifier. Experimental results show that the proposed method obtains a good performance with a small number of features compared to the existing methods.

AN ALGORITHMIC APPROACH TO THE MARKOV CHAIN WITH TRANSITION PROBABILITY MATRIX OF UPPER BLOCK-HESSENBERG FORM

  • Shin, Yang-Woo;Pearce, C.E.M.
    • Journal of applied mathematics & informatics
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    • v.5 no.2
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    • pp.403-426
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    • 1998
  • We present an algorithm to find an approximation for the stationary distribution for the general ergodic spatially-inhomogeneous block-partitioned upper Hessenberg form. Our approximation makes use of an associated upper block-Hessenberg matrix which is spa-tially homogeneous except for a finite number of blocks. We treat the MAP/G/1 retrial queue and the retrial queue with two types of customer as specific instances and give some numerical examples. The numerical results suggest that our method is superior to the ordinary finite-truncation method.

Probabilistic Assessment of Drought Characteristics based on Homogeneous Hidden Markov Model (동질성 은닉 마코프 모형을 적용한 가뭄특성의 확률론적 평가)

  • Yoo, Ji-Young;Kwon, Hyun-Han;Kim, Tae-Woong;Lee, Seung-Oh
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.1
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    • pp.145-153
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    • 2014
  • Several studies regarding drought indices and criteria have been widely studied in the literature. If one defines the onset, severity, and end of droughts, in general, a certain threshold needs to be set to assess the drought events. However, the uncertainty associated with the threshold is a critical problem in drought analysis. To take full advantage of the inherent features in the rainfall series, a Hidden Markov Model (HMM) based probabilistic drought analysis was proposed rather than using the existing threshold based analysis. As a result, the proposed HMM based probabilistic drought analysis scheme shows better performance in terms of defining drought state and understanding underlying characteristics of the drought. In addition, the HMM based approach is capable of quantifying the uncertainties associated with the classifying meteorological drought condition in a systematic way.

A study on the Efficient Rate Control Scheme Based on Received Power Level for Mobile Multimedia Streaming System (무선 이동통신 망에서의 효과적인 영상 통신을 위한 전송 신호 세기 기반의 비트율 제어 방법 연구)

  • Jeong, Jae-Yun;Ha, Le Thanh;Duong, Dinh Trieu;Kim, Hye-Soo;Ko, Sung-Jea
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.265-266
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    • 2006
  • In this paper, we propose an efficient rate control scheme based on the received power level to overcome a quality degradation of video under time varying channel condition caused by the movement of mobile devices. First, we statistically obtain the relation between the PLR and the received power level. With this information and the sequences of received power level, we calculate the transition probability for the Markov Channel Model. Then, with using Markov chain rule, we obtain the probability where the channel condition remains in a good state and finally find the efficient target bit rate by multiplying it by the offered bandwidth when the network access has begun. We use TMN8 to adjust the bit rate to our proposed outcome. Experimental results show that the proposed method can efficiently enhance the video quality and provide better PSNR performance than with only using TMN8 rate control method.

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Inference of the Probability Distribution of Phase Difference and the Path Duration of Ground Motion from Markov Envelope (Markov Envelope를 이용한 지진동의 위상차 확률분포와 전파지연시간의 추정)

  • Choi, Hang;Yoon, Byung-Ick
    • Journal of the Earthquake Engineering Society of Korea
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    • v.26 no.5
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    • pp.191-202
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    • 2022
  • Markov envelope as a theoretical solution of the parabolic wave equation with Markov approximation for the von Kármán type random medium is studied and approximated with the convolution of two probability density functions (pdf) of normal and gamma distributions considering the previous studies on the applications of Radiative Transfer Theory (RTT) and the analysis results of earthquake records. Through the approximation with gamma pdf, the constant shape parameter of 2 was determined regardless of the source distance ro. This finding means that the scattering process has the property of an inhomogeneous single-scattering Poisson process, unlike the previous studies, which resulted in a homogeneous multiple-scattering Poisson process. Approximated Markov envelope can be treated as the normalized mean square (MS) envelope for ground acceleration because of the flat source Fourier spectrum. Based on such characteristics, the path duration is estimated from the approximated MS envelope and compared to the empirical formula derived by Boore and Thompson. The results clearly show that the path duration increases proportionately to ro1/2-ro2, and the peak value of the RMS envelope is attenuated by exp (-0.0033ro), excluding the geometrical attenuation. The attenuation slope for ro≤100 km is quite similar to that of effective attenuation for shallow crustal earthquakes, and it may be difficult to distinguish the contribution of intrinsic attenuation from effective attenuation. Slowly varying dispersive delay, also called the medium effect, represented by regular pdf, governs the path duration for the source distance shorter than 100 km. Moreover, the diffraction term, also called the distance effect because of scattering, fully controls the path duration beyond the source distance of 300 km and has a steep gradient compared to the medium effect. Source distance 100-300 km is a transition range of the path duration governing effect from random medium to distance. This means that the scattering may not be the prime cause of peak attenuation and envelope broadening for the source distance of less than 200 km. Furthermore, it is also shown that normal distribution is appropriate for the probability distribution of phase difference, as asserted in the previous studies.

A Web Usage Prediction Model by Transition Probability Matrix (전이 확률 행렬에 의한 웹 사용 예측 모델)

  • 김영희;김응모;정명숙;강우준
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.10b
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    • pp.31-33
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    • 2004
  • 웹 사용에 대한 다음 요구 사항을 예측하기 위한 마이닝 방법으로 연관규칙이나 순차 패턴 등이 많이 사용되고 있지만, 이러한 방법들은 생성된 규칙들의 지지도(Support)나 신뢰도(Confidence)에 의한 예측만을 고려하기 때문에 정확한 예측을 하기 어려운 단점을 가지고 있다. 따라서, 본 논문에서는 빈도 수에 의한 Markov model을 기반으로 하여 웹 로그 파일에 저장된 사용자들의 행동 패턴에 따라 생성되어지는 여러 형태의 규칙 유형을 찾아내고, 사용 빈도 수를 이용한 전이 확률 행렬에 따른 다음 요구사항을 정확하게 예측할 수 있는 모델을 제시하고자 한다. 그 결과 여러 형태의 규칙 유형을 $K^{th}$ -order Markov 과정에서 효율적으로 발견해 낼 수 있다.

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Delay of a Message in a Time-Varying Bluetooth Link (시변 블루투스 링크에서 메시지의 지연시간)

  • Jong, Myoung-Soon;Park, Hong-Seong
    • Journal of Industrial Technology
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    • v.23 no.A
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    • pp.41-46
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    • 2003
  • Because the quality of a radio link in real environment is generally varied with time, there is a difference between the delay in the real environment and one obtained from the analytic model where a time-varying link model is not used as a link model for a Bluetooth. This paper analyzes the transmission delay of a message in the time-varying radio link model for the Bluetooth. The time-varying radio link is modeled with a two-state Markov model. The mean transmission delay of the message is analytically obtained in terms of the arrival rate of the message, the state transition probability in the Markov model, and the packet error rate.

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Spectral Clustering with Sparse Graph Construction Based on Markov Random Walk

  • Cao, Jiangzhong;Chen, Pei;Ling, Bingo Wing-Kuen;Yang, Zhijing;Dai, Qingyun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.7
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    • pp.2568-2584
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    • 2015
  • Spectral clustering has become one of the most popular clustering approaches in recent years. Similarity graph constructed on the data is one of the key factors that influence the performance of spectral clustering. However, the similarity graphs constructed by existing methods usually contain some unreliable edges. To construct reliable similarity graph for spectral clustering, an efficient method based on Markov random walk (MRW) is proposed in this paper. In the proposed method, theMRW model is defined on the raw k-NN graph and the neighbors of each sample are determined by the probability of the MRW. Since the high order transition probabilities carry complex relationships among data, the neighbors in the graph determined by our proposed method are more reliable than those of the existing methods. Experiments are performed on the synthetic and real-world datasets for performance evaluation and comparison. The results show that the graph obtained by our proposed method reflects the structure of the data better than those of the state-of-the-art methods and can effectively improve the performance of spectral clustering.

Novel Approach for Modeling Wireless Fading Channels Using a Finite State Markov Chain

  • Salam, Ahmed Abdul;Sheriff, Ray;Al-Araji, Saleh;Mezher, Kahtan;Nasir, Qassim
    • ETRI Journal
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    • v.39 no.5
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    • pp.718-728
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    • 2017
  • Empirical modeling of wireless fading channels using common schemes such as autoregression and the finite state Markov chain (FSMC) is investigated. The conceptual background of both channel structures and the establishment of their mutual dependence in a confined manner are presented. The novel contribution lies in the proposal of a new approach for deriving the state transition probabilities borrowed from economic disciplines, which has not been studied so far with respect to the modeling of FSMC wireless fading channels. The proposed approach is based on equal portioning of the received signal-to-noise ratio, realized by using an alternative probability construction that was initially highlighted by Tauchen. The associated statistical procedure shows that a first-order FSMC with a limited number of channel states can satisfactorily approximate fading. The computational overheads of the proposed technique are analyzed and proven to be less demanding compared to the conventional FSMC approach based on the level crossing rate. Simulations confirm the analytical results and promising performance of the new channel model based on the Tauchen approach without extra complexity costs.