• Title/Summary/Keyword: probability of transition

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Isolated word recognition using the SOFM-HMM and the Inertia (관성과 SOFM-HMM을 이용한 고립단어 인식)

  • 윤석현;정광우;홍광석;박병철
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.6
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    • pp.17-24
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    • 1994
  • This paper is a study on Korean word recognition and suggest the method that stabilizes the state-transition in the HMM by applying the `inertia' to the feature vector sequences. In order to reduce the quantized distortion considering probability distribution of input vectors, we used SOFM, an unsupervised learning method, as a vector quantizer, By applying inertia to the feature vector sequences, the overlapping of probability distributions for the response path of each word on the self organizing feature map can be reduced and the state-transition in the Hmm can be Stabilized. In order to evaluate the performance of the method, we carried out experiments for 50 DDD area names. The results showed that applying inertia to the feature vector sequence improved the recognition rate by 7.4% and can make more HMMs available without reducing the recognition rate for the SOFM having the fixed number of neuron.

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A New Analytical Algorithm of Timed Net with Probabilities of Choices and Its Application (이벤트의 선택 확률을 고려한 시간 넷의 분석 알고리즘 및 응용)

  • Yim Jae-Geol;Joo Jae-Hun
    • Journal of the Korean Operations Research and Management Science Society
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    • v.30 no.4
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    • pp.99-115
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    • 2005
  • For an analysis of the performance of a computer system, the minimum cycle time method has been widely used. The minimum cycle time method is a mathematical technique with which we can find the minimum duration time needed to fire all the transitions at least once and coming back to the Initial marking in a timed net. A timed net is a modified version of a Petri net where a transition is associated with a delay time. In the real world, an event is associated with a probability of occurrence. However, a timed net is not equipped with any facility of specifying probability of event occurrence. Therefore, the minimum cycle time method applied on a timed net can easily overlook probabilities of occurrences of events and yield a wrong result. We are proposing 'Timed Net with Probabilities of Choices' where a transition can be associated with both delay time and a probability of occurrence. We also introduce an algorithm for minimum cycle time analysis on a 'Timed Net with Probabilities of Choices'. As an example of application, we are performing an analysis of the location based service system using 'Timed Net with Probabilities of Choices'.

Flow pattern characteristics in vertical two phase flow by PDF and signals from conductance probe (確率密度函數와 電導 Prode信號에 의한 垂直二相流의 流動樣式特性)

  • Son, Byung-Jin;Kim, In-Suhk;Lee, Jin
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.10 no.6
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    • pp.814-822
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    • 1986
  • Flow patterns and its transitions in vertical two phase flow of air-water isothermal flow are identified objectively by void output signals and moments computed from the Probability Density Function which is associated with the statistical measurement for time average local void fractions using conductance probe. It has been shown that the probe output signals, PDF distributions and its moments are deterministic criteria of flow pattern and transition classification.

Random sequence synchronization failure detection algorithm for synchronous stream cipher system using RMVD (RMVD를 이용하는 동기식 스트림 암호 데이터 통신시 난수동기 이탈 검출 알고리듬)

  • 박종욱
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.10 no.3
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    • pp.29-36
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    • 2000
  • It is very import role to increase communication quality that fast detection of random sequence synchronization fail in synchronous stream cipher system using initial synchronization mode. Generally it sends additional information to detect random sequency synchronization fail. But we can't transmit additional informations to decide synchronization fail in a system using RMVD to correct channel error. In this paper we propose a method to detect synchronization fail in the receiver even though a system using RMVD has no margin to send additional information, For detecting random sequency synchronization fail we decipher receiver data analyze probability of transition rate for pre-determined period and decide synchronization fail using calculated transition rate probability. This proposed method is fast very reliable and robust in noisy channel and is easily implemented with hardware.

An Approximate algorithm for the analysis of the n heterogeneous IBP/D/l queuing model (다수의 이질적 IBP/D/1큐잉 모형의 분석을 위한 근사 알고리즘)

  • 홍석원
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.4 no.3
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    • pp.549-555
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    • 2000
  • We propose an approximate algorithm to analyze the queuing system with n bursty and heterogeneous arrival processes. Each input process is modeled by Interrupted Bernoulli Process(IBP). We approximate N arrival processes by a single state variable and subsequently simplify the transition probability matrix of the Markov chain associated with these N arrival processes. Using this single state variable of arrival processes, we describe the state of the queuing system and analyze the system numerically with the reduced transition probability matrix. We compute the queue length distribution, the delay distribution, and the loss probability. Comparisons with simulation data show that the approximation algorithm has a good accuracy.

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Meeting of Gauss and Shannon at Coin Leaf in 5G Massive MIMO (5G Massive MIMO에서 가우스(Gauss)와 샤논(Shannon)이 동전 한 닢에서 만남)

  • Kim, Jeong-Su;Lee, Moon-Ho;Park, Daechul
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.18 no.2
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    • pp.89-103
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    • 2018
  • A genius "Prince of Mathematician" Gaussian and "Father of Communication" Shannon comes up with the creative idea of motivation to meet each other? The answer is a coin leaf. Gaussian found some creative ideas in the matter of obtaining a sum of 1 to 100. This is the same as the probability distribution curve when a coin leaf is thrown. Shannon extended the Gaussian probability distribution to define the entropy, taking the source symbol and the reciprocal logarithm to obtain the weighted average. These where the genius Gaussian and Shannon meet in the same coin leaf. This paper focuses on this point, and easily proves Gaussian distribution and Shannon entropy. As an application example, we have obtained the capacity and transition probability of Jeongju seminal vesicle, and the Shannon channel capacity is 1 when the equivalent transition probability is 1/2.

Analysis of Land Conversion Characteristics in Process of Farmland Loss and Urbanization by Distance from Center of City Using Detailed Digital Land Use - With Representative Big Cities and Their Fringe Areas in Japan - (정밀수치정보를 이용한 도시중심에서 거리별 농지손실 및 도시화과정의 토지전용 특성 분석 - 일본의 대표적 도시주변지역을 중심으로 -)

  • Kim, Dae-Sik
    • Journal of Korean Society of Rural Planning
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    • v.9 no.1 s.18
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    • pp.65-75
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    • 2003
  • As a pre-step research to make land-use planning in the region level, this study aims to analyze some probability pattern representing transition probabilities from farmland to others using the sequential detailed digital land-use maps. Kinki and Chubu regions of Japan, which have Osaka and Nagoya cities as their center places respectively, were selected as test regions in this study. The 10m grid land-use maps for four time series at every 5 year from 1977 to 1992 were used. In this study, the regions were divided into three sub-areas 10km, 20km, and 30km according to distance from center cities, respectively. The correlation coefficient (CC) between sub-areas with same distance in the two regions was calculated to analyze whether or not the two regions have common points in the pattern of land-use conversion probability from farmland to other types. The probability distribution of the converted areas which were moved to the urbanized area (residential, commercial, industrial, road, park and public facility areas) was about $40{\sim}70%$ for both all periods and sub-areas. According to distance from city centers, the probability moved to the urbanized area was about 60% at 10km area, and 40% at the 30km area, which means that the values we decreased gradually, while in the case moved to the forest and the etc areas, the values were increased slightly. The CC analysis from the paddy field and the dry field to the others separately showed that there is high correlation in the probability pattern between the two regions.

Korean Word Recognition using the Transition Matrix of VQ-Code and DHMM (VQ코드의 천이 행렬과 이산 HMM을 이용한 한국어 단어인식)

  • Chung, Kwang-Woo;Hong, Kwang-Seok;Park, Byung-Chul
    • The Journal of the Acoustical Society of Korea
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    • v.13 no.4
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    • pp.40-49
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    • 1994
  • In this paper, we propose methods for improving the performance of word recognition system. The ray stratey of the first method is to apply the inertia to the feature vector sequences of speech signal to stabilize the transitions between VQ cdoes. The second method is generating the new observation probabilities using the transition matrix of VQ codes as weights at the observation probability of the output symbol, so as to take into account the time relation between neighboring frames in DHMM. By applying the inertia to the feature vector sequences, we can reduce the overlapping of probability distribution of the response paths for each word and stabilize state transitions in the HMM. By using the transition matrix of VQ codes as weights in conventional DHMM. we can divide the probability distribution of feature vectors more and more, and restrict the feature distribution to a suitable region so that the performance of recognition system can improve. To evaluate the performance of the proposed methods, we carried out experiments for 50 DDD area names. As a result, the proposed methods improved the recognition rate by $4.2\%$ in the speaker-dependent test and $12.45\%$ in the speaker-independent test, respectively, compared with the conventional DHMM.

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Prediction for the Spatial Distribution of Occupational Employment by Applying Markov Chain Model (마르코프 체인 모형을 이용한 직종별 취업자의 공간적 분포 변화 예측)

  • Park, So Hyun;Lee, Keumsook
    • Journal of the Korean Geographical Society
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    • v.51 no.4
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    • pp.525-539
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    • 2016
  • This study attempts to predict the changes in the spatial distribution of occupational employment in Korea by applying Markov Chain Model. For the purpose we analyze the job-related migration pattern and estimate the transition probability with the last six years job-related migration data. By applying the Chapman-Kolmogorov equation based on the transition probability, we predict the changes in the spatial distribution of occupational employment for the next ten years. The result reveals that the employment of professional jobs is predicted to increase at every city and region except Seoul, while the employment of elementary labor jobs is predicted to increase slightly in Seoul. In particular, Gangwon-do and Chuncheongdo are predicted to increase in the employment of all occupational jobs.

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On Weak Convergence of Some Rescaled Transition Probabilities of a Higher Order Stationary Markov Chain

  • Yun, Seok-Hoon
    • Journal of the Korean Statistical Society
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    • v.25 no.3
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    • pp.313-336
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    • 1996
  • In this paper we consider weak convergence of some rescaled transi-tion probabilities of a real-valued, k-th order (k $\geq$ 1) stationary Markov chain. Under the assumption that the joint distribution of K + 1 consecutive variables belongs to the domain of attraction of a multivariate extreme value distribution, the paper gives a sufficient condition for the weak convergence and characterizes the limiting distribution via the multivariate extreme value distribution.

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