gesture and motion recognition are needed for a variety of applications. the use of human hand motions as a natural interface tool has motivated researchers to conduct research in the modeling, analysis and recognition of various hand movements. in particular, human-computer intelligent interaction has been a focus of research in vision-based gesture recognition. in this work, we introduce a 3-...

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...

nowadays, hidden markov models are extensively utilized for modeling stochastic processes. these models help researchers establish and implement the desired theoretical foundations using markov algorithms such as forward one. however, using stability hypothesis and the mean statistic for determining the values of markov functions on unstable statistical data set has led to a significant reducti...

Fractal stochastic processes are examples of semi-Markov processes where the signal behaviour is a function of the prefiltering bandwidth. In this paper we develop schemes for estimating such fractal models when they are hidden (imbedded) in noise. We reformulate this hidden fractal model (H FM) problem in the scalar case as a higher order scalar or first order 2-vector homogeneous hidden Marko...

Discriminative learning techniques for sequential data have proven to be more effective than generative models for named entity recognition, information extraction, and other tasks of discrimination. However, semi-supervised learning mechanisms that utilize inexpensive unlabeled sequences in addition to few labeled sequences – such as the Baum-Welch algorithm – are available only for generative...

in this paper we address the issue of recognizing farsi handwritten words. two types of gradient features are extracted from a sliding vertical stripe which sweeps across a word image. these are directional and intensity gradient features. the feature vector extracted from each stripe is then coded using the self organizing map (som). in this method each word is modeled using the discrete hidde...

mobile ad-hoc networks have attracted a great deal of attentions over the past few years. considering their applications, the security issue has a great significance in them. security scheme utilization that includes prevention and detection has the worth of consideration. in this paper, a method is presented that includes a multi-level security scheme to identify intrusion by sensors and authe...

We investigate two statistical-detection problems, change-point detection and pattern matching in plasma etch endpoint detection. Our approach is based on a segmental semi-Markov model framework. In the change-point detection problem, the changepoint corresponds to state switching in the model. For pattern matching, the pattern is approximated as a sequence of linear segments which are then mod...

Due to the effective role of Markov models in customer relationship management (CRM), there is a lack of comprehensive literature review which contains all related literatures. In this paper the focus is on academic databases to find all the articles that had been published in 2011 and earlier. One hundred articles were identified and reviewed to find direct relevance for applying Markov models...

Hidden Markov chains (HMC) are a very powerful tool in hidden data restoration and are currently used to solve a wide range of problems. However, when these data are not stationary, estimating the parameters, which are required for unsupervised processing, poses a problem. Moreover, taking into account correlated non-Gaussian noise is difficult without model approximations. The aim of this pape...