as is well known, estimating parameters of the tree-parameter weibull distribution is a complicated task and sometimes contentious area with several methods vying for recognition. weibull distribution involves in reliability studies frequently and has many applications in engineering. however estimating the parameters of weibull distribution is crucial in classical ways. this distribution has t...

As is well known, estimating parameters of the tree-parameter weibull distribution is a complicated task and sometimes contentious area with several methods vying for recognition. Weibull distribution involves in reliability studies frequently and has many applications in engineering. However estimating the parameters of Weibull distribution is crucial in classical ways. This distribution has t...

The method presented here is aimed to a direct fast setting of the parameters of a RBF network for function approximation. It is based on a hierarchical gridding of the input space; additional layers of Gaussians at lower scales are added where the residual error is higher. The number of the Gaussians of each layer and their variance are computed from considerations grounded in the linear filte...

An estimate of quark mass parameters suitable for the study of chiral symmetry breaking effects is made using exact GoldbergerTreiman relations for the Goldstone bosons which appear in the WeinbergSalam theory when the gauge coupling is set to zero. The numbers obtained are m U = 13.75 5.9 MeV, md = 24.7t12.9 MeV, and ms = 4972 299 MeV. Consistency of the various Goldberger-Treiman relations wi...

This paper presents algorithms for identifying parameters of an N degrees-of-freedom robotic manipulator. First, we outline the fundamental properties of the Newton-Euler formulation of robot dynamics from the view point of parameter identification. We then show that the Newton-Euler model which is nonlinear in the dynamic parameters can be transformed into an equivalent modified model which is...

The rapid growth in the amount of molecular genetic data being collected will, in many cases, require the development of new analytic methods for the analysis of that data. In this paper we explore the feasibility of using machine learning algorithms, in particular neural networks, to estimate two evolutionary parameters of great interest: mutation and recombination rates. We show that this is ...

This paper presents algorithms for identifying parameters of an N degrees-of-freedom robotic manipulator. First, we outline the fundamental properties of the Newton-Euler formulation of robot dynamics from the view point of parameter identification. We then show that the Newton-Euler model which is nonlinear in the dynamic parameters can be transformed into an equivalent modified model which is...