The performance of many traffic control strategies depends on how much the traffic flow models are accurately calibrated. One of the most applicable traffic flow model in traffic control and management is LWR or METANET model. Practically, key parameters in LWR model, including free flow speed and critical density, are parameterized using flow and speed measurements gathered by inductive loop d...

In this paper we consider parameter estimation of general stochastic nonlinear statespace models using the Maximum Likelihood method. This is accomplished via the employment of an Expectation Maximisation algorithm, where the essential components involve a particle smoother for the expectation step, and a gradient-based search for the maximisation step. The utility of this method is illustrated...

background: in this study, quantitative 32p bremsstrahlung planar and spect imaging and consequent dose assessment were carried out as a comprehensive phantom study to define an appropriate method for accurate dosimetry in clinical practice. materials and methods: ct, planar and spect bremsstrahlung images of jaszczak phantom containing a known activity of 32p were acquired. in addition, phanto...

Parameter estimation in dynamic systems finds applications in various disciplines, including system biology. The well-known expectation-maximization (EM) algorithm is a popular method and has been widely used to solve system identification and parameter estimation problems. However, the conventional EM algorithm cannot exploit the sparsity. On the other hand, in gene regulatory network inferenc...

In this paper we proposed deterministic maximum likelihood approach for estimating the direction of arrival and range parameters of the neareld sources. Direct maximum likelihood estimation of neareld source parameters results in complicated multi-parameter optimization problems , we therefore reformulated the estimation problem in terms of actual-data sample, called the incomplete data and a h...

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...

Performance of Language Identification (LID) System using Gaussian Mixture Models (GMM) is limited by the convergence of Expectation Maximization (EM) algorithm to local maxima. In this paper an LID system is described using Gaussian Mixture Models for the extracted features which are then trained using Split and Merge Expectation Maximization Algorithm that improves the global convergence of E...

The maximum entropy principle (MEP), which has been popular in the modeling of droplet size and velocity distribution in sprays, is, strictly speaking, only applicable for isolated systems in thermodynamic equilibrium; whereas the spray formation processes are irreversible and non-isolated with interaction between the atomizing liquid and its surrounding gas medium. In this study, a new model f...

We link the weighted maximum entropy and the optimization of the expected Fβmeasure, by viewing them in the framework of a general common multi-criteria optimization problem. As a result, each solution of the expected Fβ-measure maximization can be realized as a weighted maximum likelihood solution a well understood and behaved problem. The specific structure of maximum entropy models allows us...