Nowadays, the source localization has been widely applied for wireless sensor networks. The Gaussian mixture model has been adopted for maximum-likelihood (ML) source localization ...
Point Distribution Models are useful tools for modelling the variability of particular classes of shapes. A common approach is to apply a Principle Component Analysis to the data,...
James Orwell, Darrel Greenhill, Jonathan D. Rymel,...
In a variety of disciplines such as social sciences, psychology, medicine and economics, the recorded data are considered to be noisy measurements of latent variables connected by...
The mixmod (mixture modeling) program fits mixture models to a given data set for the purposes of density estimation, clustering or discriminant analysis. A large variety of algor...
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...