— In this paper, we perform a complete asymptotic performance analysis of the stochastic approximation algorithm (denoted subspace network learning algorithm) derived from Oja’...
- A dynamical neural model that is strongly biologically motivated is applied to learning and retrieving binary patterns. This neural network, known as Freeman’s Ksets, is traine...
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
We consider the problem of multirate network design with point-to-multipoint communications. We give a mathematical formulation for this problem. Using approximations, we show that...
Abstract- This paper presents a RWA strategy based on the stochastic estimation of the Effective Number of Available Wavelengths (ENAW) along interdomain paths. We propose an appro...