We consider the problem of verifying the identity of a distribution: Given the description of a distribution over a discrete support p = (p1, p2, . . . , pn), how many samples (independent draws) must one obtain from an unknown distribution, q, to distinguish, with high probability, the case that p = q from the case that the total variation distance (L1 distance) ||p− q||1 ≥ ε? We resolve this ...

We develop a gradient-like algorithm to minimize sum of peer objective functions based on coordination through interconnection network. The admits two stages: the first is constitute gradient, possibly with errors, for updating locally replicated decision variables at each and second used error-free averaging synchronizing local replicas. Unlike many related algorithms, errors permitted in our ...

The purpose of this paper is to study and give the necessary andsufficient condition of strong convergence of the multi-step iterative algorithmwith errors for a finite family of generalized asymptotically quasi-nonexpansivemappings to converge to common fixed points in Banach spaces. Our resultsextend and improve some recent results in the literature (see, e.g. [2, 3, 5, 6, 7, 8,11, 14, 19]).

All integer data types in programs (such as int, short, byte) have an underlying finite representation in hardware. This finiteness can result in subtle integer-overflow errors that are hard to reason about both for humans and analysis tools alike. As a first step towards finding such errors automatically, we will describe two modular arithmetic decision procedures for reasoning about bounded i...

In this paper we study the bounded perturbation resilience of the extragradient and the subgradient extragradient methods for solving a variational inequality (VI) problem in real Hilbert spaces. This is an important property of algorithms which guarantees the convergence of the scheme under summable errors, meaning that an inexact version of the methods can also be considered. Moreover, once a...

In this article, we investigate a constrained optimal coordination problem for class of heterogeneous nonlinear multi-agent systems described by high-order dynamics subject to both unknown nonlinearities and external disturbances. Each agent has private objective function steady-state constraint about its output. We develop composite distributed controller each combination internal model neural...

parameter estimation of the nonlinear muskingum model is a highly nonlinear optimization problem. although various techniques have been applied to optimize the coefficients of the nonlinear muskingum flood routing models, but an efficient method for this purpose in the calibration process is still lacking. the accuracy of artificial bee colony (abc) algorithm is investigated in this paper to op...

in this research, performance of pattern search algorithm (ps) was investigated in order to optimize the nonlinear muskingum model parameters in contrast with the general algorithms, for wilson and karoun floods routing. wilson flood routing has been chosen to compare the ability of ps algorithm with other algorithms and, karoun flood routing has been chosen for a better evaluation of ps. the r...