An algorithm of incremental approximation of functions in a normed linearspace by feedforward neural networks is … the weight decay method, for optimizing the size andweights of a network in each iteration step of the algorithm. Two … alternatives, recursively incremental and generally incremental, are proposed. In the generally incremental case, the algorithm …

these proposal densities are used in an independent Metropolis-Hastings algorithm. A particular feature of our approach is … that smoothed estimates of the states and the marginal likelihood are obtained directly as an output of the algorithm. Our …

This paper examines maximum likelihood estimation via hill climbing and the expectations maximization (EM) algorithm in … technique is shown to significantly reduce the computational demands of the EM algorithm relative to a Davidon Fletcher Powell …