This thesis develops a hybrid decentralized formation control framework to coordinate multiple mobile robots with nonholonomic constraints. The proposed approach deploys a control theoretic bottom-up approach where, some low level behavior based controllers are coordinated by a discrete event system with supervisory control. The robots are required to navigate in an unstructured environment wit...

The equilibria of strategic games with many semi-anonymous players have a strong ex-post Nash property. Even with perfect hindsight about the realized types and selected actions of all his opponents, no player has an incentive to revise his own chosen action. This is illustrated for normal form and for one shot Baysian games with statistically independent types, provided that a certain continui...

This paper addresses the problem of creating probabilistic brain atlases from manually labeled training data. We propose a general mesh-based atlas representation, and compare different atlas models by evaluating their posterior probabilities and the posterior probabilities of their parameters. Using such a Baysian framework, we show that the widely used "average" brain atlases constitute relat...

In this paper, we investigate some inferential properties of the upper record Lomax distribution. Also, we will estimate the upper record of the Lomax distribution parameters using methods, Moment (MME), Maximum Likelihood (MLE), Kullback-Leibler Divergence of the Survival function (DLS) and Baysian. Finally, we will compare these methods using the Monte Carlo simulation.

This paper proposes a novel method of estimating 3-D hand posture from images observed in complex backgrounds. Conventional methods often cause mistakes by mis-matches of local image features. Our method considers possibility of the mis-match between each posture model appearance and the other model appearances in a Baysian stochastic estimation form by introducing a novel likelihood concept “M...

This thesis analyzes the various modeling techniques for face recognition that are available to us within the eigenface framework and experiments with different methods that can be used to match faces using eigenfaces. It presents a probabilistic approach to matching faces and demonstrates it's superiority over other methods. It also carries out comprehensive parameter exploration experiments t...

A kernel method for realizing Bayes’ rule is proposed, based on representations of probabilities in reproducing kernel Hilbert spaces. Probabilities are uniquely characterized by the mean of the canonical map to the RKHS. The prior and conditional probabilities are expressed in terms of RKHS functions of an empirical sample: no explicit parametric model is needed for these quantities. The poste...

Supervised classification procedures are developed and applied to synthetic aperture radar (SAR) in order to identify their various earth terrain components. An implementation of the maximum a posteriori (MAP) and the maximum likelihood (ML) algorithms are presented. These two techniques need a statistic model for the conditional distribution of the polarimetric complex data. Many previous stud...

Many databases involve ordered discrete responses in a temporal and spatial context, including, for example, land development intensity levels, vehicle ownership, and pavement conditions. An appreciation of such behaviors requires rigorous statistical methods, recognizing spatial effects and dynamic processes. This study develops a dynamic spatial ordered probit (DSOP) model in order to capture...