Abstract. Self-Organizing Map (SOM) is an unsupervised learning neural network and it is used for preserving the structural relationships in the data without prior knowledge. SOM h...
—We consider a cognitive radio network with distributed multiple secondary users, where each user independently searches for spectrum opportunities in multiple channels without e...
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. denite clause programs containing probabilistic facts with a ...
We consider the problem of image representation and clustering. Traditionally, an n1 × n2 image is represented by a vector in the Euclidean space Rn1×n2 . Some learning algorith...
This work deals with a new technique for the estimation of the parameters and number of components in a finite mixture model. The learning procedure is performed by means of a expe...