The asymptotic behavior of stochastic gradient algorithms is studied. Relying on some results of differential geometry (Lojasiewicz gradient inequality), the almost sure pointconve...
Abstract-- We study the convergence rate of average consensus algorithms in networks with stochastic communication failures. We show how the system dynamics can be modeled by a dis...
A neural-based method for source separation in nonlinear mixture is proposed in this paper. A cost function, which consists of the mutual information and partial moments of the out...
— This paper studies consensus seeking over noisy networks with time-varying noise statistics. Stochastic approximation type algorithms can ensure consensus in mean square and wi...