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» On the convergence of Hill's method
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TNN
2008
82views more  TNN 2008»
15 years 1 months ago
Deterministic Learning for Maximum-Likelihood Estimation Through Neural Networks
In this paper, a general method for the numerical solution of maximum-likelihood estimation (MLE) problems is presented; it adopts the deterministic learning (DL) approach to find ...
Cristiano Cervellera, Danilo Macciò, Marco ...
AMC
2004
105views more  AMC 2004»
15 years 1 months ago
Block matrix Sinc-Galerkin solution of the wind-driven current problem
A block matrix formulation is presented for the Sinc-Galerkin technique applied to the wind-driven current problem from oceanography. The block matrix form is used to determine an...
Sanoe Koonprasert, Kenneth L. Bowers
IJON
2002
105views more  IJON 2002»
15 years 1 months ago
Separation of sources using simulated annealing and competitive learning
This paper presents a new adaptive procedure for the linear and non-linear separation of signals with non-uniform, symmetrical probability distributions, based on both simulated a...
Carlos García Puntonet, Ali Mansour, Christ...
CGF
1999
79views more  CGF 1999»
15 years 1 months ago
Stochastic Iteration for Non-diffuse Global Illumination
This paper presents a single-pass, view-dependent method to solve the rendering equation, using a stochastic iterational scheme where the transport operator is selected randomly i...
László Szirmay-Kalos
MP
2002
84views more  MP 2002»
15 years 1 months ago
A decomposition procedure based on approximate Newton directions
The efficient solution of large-scale linear and nonlinear optimization problems may require exploiting any special structure in them in an efficient manner. We describe and analy...
Antonio J. Conejo, Francisco J. Nogales, Francisco...