Distributed or decentralized estimation of covariance, and distributed principal component analysis have been introduced studied in the signal processing community recent years, applications array indicated some detail. Inspired by these, this paper provides a detailed development several algorithms for processing. New are proposed DOA methods like root-MUSIC, total least squares-ESPRIT, FOCUSS...

The estimation of the full state a nonautonomous semilinear parabolic equation is achieved by Luenberger-type dynamical observer. derived from an output given finite number average measurements on small regions. estimate observer converges exponentially to real state, as time increases. result semiglobal in sense that error dynamics can be made stable for arbitrary initial condition, provided l...

Reward-Weighted Regression (RWR) belongs to a family of widely known iterative Reinforcement Learning algorithms based on the Expectation-Maximization framework. In this family, learning at each iteration consists sampling batch trajectories using current policy and fitting new maximize return-weighted log-likelihood actions. Although RWR is yield monotonic improvement under certain circumstanc...

Extending the results of a previous work, we consider a class of discrete lattice gas models in a finite interval whose bulk dynamics consists of stochastic exchanges which conserve the particle number, and with stochastic dynamics at the boundaries chosen to model infinite particle reservoirs at fixed chemical potentials. We establish here the local equilibrium structure of the stationary meas...

In the state-based self-stabilizing algorithmic paradigm for distributed computing, each node has only a local view of the system (seeing its neighbors’ states), yet in a finite amount of time the system converges to a global state satisfying some desired property. In this paper we introduce a general mechanism that allows a node to act only on correct distance-two knowledge, provided there are...

Children learn to ride a bicycle by using training wheels. They are actually trying to learn one task (riding without training wheels) by training another one. In general, solving a difficult problem can be facilitated by training other problems. This is the basic idea of shaping. It is essential to ensure that spending time on the modified task will help solving the original one. In this paper...

In this note we describe and evaluate the performance of a novel approach to information recovery that involves consecutive projection onto convex sets (POCS). The method is applied to a time series of medical image data and the results are compared to images reconstructed using the standard POCS reconstruction method. The consecutive POCS method converges in a desired step-wise manner producin...

This paper investigates the problem of robust output regulation control with prospected transient property for strict feedback systems. By employing internal model principle, a can be transformed to stabilization new constraint. Then, by constructing speed function and adopting barrier Lyapunov technique, dynamic controller designed not only drive error closed-loop system entering into prescrib...

In this paper we propose and analyze a hp-adaptive discontinuous finite element method for computing the band structure of 2D periodic photonic crystals. The problem can be reduced to the computation of the discrete spectrum of each member in a family of periodic Hermitian eigenvalue problems on the primitive cell, parametrised by a two-dimensional parameter the quasimomentum. We propose a resi...

We study the convergence of the proximal algorithm applied to nonsmooth functions that satisfy the Lojasiewicz inequality around their generalized critical points. Typical examples of functions complying with these conditions are continuous semialgebraic or subanalytic functions. Following Lojasiewicz’s original idea, we prove that any bounded sequence generated by the proximal algorithm conver...