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The inclusion of the free-running Purkinje network in computational simulations provides a significant insight into understanding the mechanisms of cardiac pathophysiologies. However, its automatic extraction is challenging due to the presence of abundant local complexities. We thereby introduce a novel algorithm to track the Purkinje fibers in high resolution magnetic resonance (MR) images. Our formulation...
Standard hidden Markov model (HMM) and the more general dynamic Bayesian network (DBN) models assume stationarity of state transition distribution. However, this assumption does not hold for many real life events of interest. In this paper, we propose a new time sequence model that extends HMM to time varying scenario. The time varying property is realized in our model by explicitly allowing the change...
This paper describes a systematic approach to integrate the Discrete Event Specified System (DEVS) methodology into SystemC. It thus combines Model of Computation (MoC) specific properties and the features of an advanced SystemC environment. The execution of abstract system level DEVS models is comparable to pure SystemC models and is significantly faster compared to other DEVS environments. Thus,...
The method of stable random projections is an efficient tool for computing the lalpha distances using low memory, where 0 < alpha les 2 may be viewed as a tuning parameter. This method boils down to a statistical estimation task and various estimators have been proposed, based on the geometric mean, harmonic mean, and fractional power etc. This study proposes the optimal quantile estimator, whose...
In this paper optimal model of a stochastic complex system with cascade structure is presented. A recursive algorithm for recovering the model from observations performed on the system is given. Asymptotic optimality of the algorithm is studied. An application of presented approach to identification of static characteristics of chemical process in the cascade of reactors is shown. Numerical examples...
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