in this paper, an interactive model for individual normal behaviour of drivers is presented in which the mutual effect of vehicles has been incorporated. temporal features obtained from vehicles tracking and their motion history is utilized for generating a model of normal behaviour. because of non-stationarity of behaviour, hidden markov model has been used for interactive model. this model ha...

Recognizing the activities of daily living plays an important role in healthcare. It is necessary to use an adapted model to simulate the human behavior in a domestic space to monitor the patient harmonically and to intervene in the necessary time. In this paper, we tackle this problem using the hierarchical hidden Markov model for representing and recognizing complex indoor activities. We prop...

the geometric distribution of states duration is one of the main performance limiting assumptions of hidden markov modeling of speech signals. stochastic segment models, generally, and segmental hmm, specifically, overcome this deficiency partly at the cost of more complexity in both training and recognition phases. in this paper, a new duration modeling approach is presented. the main idea of ...

The air transport industry is seeking to manage risks in air travels. Its main objective is to detect abnormal behaviors in various flight conditions. The current methods have some limitations and are based on studying the risks and measuring the effective parameters. These parameters do not remove the dependency of a flight process on the time and human decisions. In this paper, we used an HMM...

An electric arc furnace (EAF) is known as nonlinear and time variant load that causes power quality (PQ) problems such as, current, voltage and current harmonics, voltage flicker, frequency changes in power system. One of the most important problems to study the EAF behavior is the choice of a suitable model for this load. Hence, in this paper, a probabilistic three-phase model is proposed base...

We study the entropy rate of a hidden Markov process, defined by observing the output of a symmetric channel whose input is a first order Markov process. Although this definition is very simple, obtaining the exact amount of entropy rate in calculation is an open problem. We introduce some probability matrices based on Markov chain's and channel's parameters. Then, we try to obtain an estimate ...

Hidden Markov Model Regression (HMMR) is an extension of the Hidden Markov Model (HMM) to regression analysis. We assume that the parameters of the regression model are determined by the outcome of a nite-state Markov chain and that the error terms are conditionally independent normally distributed with mean zero and state dependent variance. The theory of HMM regression is quite new, but some ...

We present HMM attacks, a new type of cryptanalysis based on modeling randomized side channel countermeasures as Hidden Markov Models (HMM’s). We also introduce Input Driven Hidden Markov Models (IDHMM’s), a generalization of HMM’s that provides a powerful and unified cryptanalytic framework for analyzing countermeasures whose operational behavior can be modeled by a probabilistic finite state ...