• The Transactions of the Korea Information Processing Society
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• v.7 no.6
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• pp.1852-1860
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• 2000

Distinct from the Markov random field or pseudo 2D HMM models for image analysis, this paper proposes a new model of 2D hidden Markov mesh chain(HMMM) model which subsumes the definitions of and the assumptions underlying the conventional HMM. The proposed model is a new theoretical realization of 2D HMM with the causality of top-down and left-right progression and the complete lattice constraint. These two conditions enable an efficient mesh decoding for model estimation and a recursive maximum likelihood estimation of model parameters. Those algorithms are developed in theoretical perspective and, in particular, the training algorithm, it is proved, attains the optimal set of parameters.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.491-501
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• 2006

We consider a multiple change point model with autoregressive conditional heteroscedasticity (ARCH). The model assumes that all or the part of the parameters in the ARCH equation change over time. The occurrence of the change points is modelled as the discrete time Markov process with unknown transition probabilities. The model is estimated by Markov chain Monte Carlo methods based on the approach of Chib (1998). Simulation is performed using a variant of perfect sampling algorithm to achieve the accuracy and efficiency. We apply the proposed model to the simulated data for verifying the usefulness of the model.

• Journal of the Korean Statistical Society
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• v.28 no.2
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• pp.235-251
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• 1999

In this paper we examine extremal behavior of a $textsc{k}$th-order stationary Markov chain {X\ulcorner} by considering excesses over a high level which typically appear in clusters. Excesses over a high level within a cluster define a cluster damage, i.e., a normalized sum of all excesses within a cluster, and all excesses define a damage point process. Under some distributional assumptions for {X\ulcorner}, we prove convergence in distribution of the cluster damage and obtain a representation for the limiting cluster damage distribution which is well suited for simulation. We also derive formulas for the mean and the variance of the limiting cluster damage distribution. These results guarantee a compound Poisson limit for the damage point process, provided that it is strongly mixing.

• Smart Structures and Systems
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• v.15 no.3
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• pp.735-749
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• 2015

The major difficulty of using Bayesian probabilistic inference for system identification is to obtain the posterior probability density of parameters conditioned by the measured response. The posterior density of structural parameters indicates how plausible each model is when considering the uncertainty of prediction errors. The Markov chain Monte Carlo (MCMC) method is a widespread medium for posterior inference but its convergence is often slow. The differential evolution adaptive Metropolis-Hasting (DREAM) algorithm boasts a population-based mechanism, which nms multiple different Markov chains simultaneously, and a global optimum exploration ability. This paper proposes an improved differential evolution adaptive Metropolis-Hasting algorithm (IDREAM) strategy to estimate the posterior density of structural parameters. The main benefit of IDREAM is its efficient MCMC simulation through its use of the adaptive Metropolis (AM) method with a mutation strategy for ensuring quick convergence and robust solutions. Its effectiveness was demonstrated in simulations on identifying the structural parameters with limited output data and noise polluted measurements.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.1-8
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• 2022

Supporting real-time flows with delay and throughput constraints is an important challenge for future wireless networks. In this paper, we develop an optimal scheduling scheme to optimally choose the packets to transmit. The optimal transmission strategy is based on an observable Markov decision process. The novelty of the work focuses on a priority-based probabilistic packet scheduling strategy for efficient packet transmission. This helps in providing guaranteed services to real time traffic in Heterogeneous Wireless Networks. The proposed scheduling mechanism is able to optimize the desired performance. The proposed scheduler improves the overall end-to-end delay, decreases the packet loss ratio, and reduces blocking probability even in the case of congested network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.135-138
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• 2023

In this paper, we study real-time error in the context of monitoring a binary information source through a delay system. To derive the average real-time error, we model the delay system as a discrete time Geo/D/1/1 queueing model. Using a discrete time three-dimensional Markov chain with finite state space, we analyze the queueing model. We also perform some numerical analysis on various system parameters: state transition probabilities of binary information source; transmission times; and transmission frequencies. When the state changes of the information source are positively correlated and negatively correlated, we investigate the relationship between transmission time and transmission frequency.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.9-15
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• 2010

Cognitive radio is a technology, which automatically recognizes and searches for temporally and spatially unused frequency spectrum, then actively determines the communication method, bandwidth, etc. according to the environment, thus utilizing the limited spectrum resources efficiently. In this paper, with the imperfect sensing of misdetection and false alarm, we quantitatively investigate the effects of primary and secondary user's queue on the primary and secondary users' spectrum usage through the analysis of continuous time Markov Chain. With the queue primary user's spectrum usage improved up to 18%, and the secondary user's spectrum usage improved up to 50%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.1-8
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• 2010

Wireless multimedia service through the access to mobile telephone network or data network is a vital part of contemporary life, and the demand for frequency spectrum for new services is expected to explode as the ubiquitous computing proliferate. Cognitive radio is a technology, which automatically recognizes and searches for temporally and spatially unused frequency spectrum, then actively determines the communication method, bandwidth, etc. according to the environment, thus utilizing the limited spectrum resources efficiently. In this paper, we investigate the effects of imperfect sensing, misdetection and false alarm, on the primary and secondary users' spectrum usage through the analysis of continuous time Markov Chain. We analyzed the effects of the parameters such as sensing error, offered load on the system performance.

• 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.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1219-1230
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• 2003

We analyze an integrated voice/data CDMA system, where the whole channels are divided into voice prioritized channels and voice non-prioritized channels. For real-time voice service, a preemptivc priority is granted in the voice prioritized channels. And, for delay-tolerant data service, the employment of buffer is considered. On the other hand, the transmission permission probability in best-effort packet-data service is controlled by estimating the residual capacity available for users. We build a 2-dimensional markov chain about prioritized-voice and stream-data services and accomplish numerical analysis in combination with packet-data traffic based on residual capacity equation.