Displaying similar documents to “Evolutionary training for Dynamical Recurrent Neural Networks: an application in finantial time series prediction.”

On solution sets of information inequalities

Nihat Ay, Walter Wenzel (2012)

Kybernetika

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We investigate solution sets of a special kind of linear inequality systems. In particular, we derive characterizations of these sets in terms of minimal solution sets. The studied inequalities emerge as information inequalities in the context of Bayesian networks. This allows to deduce structural properties of Bayesian networks, which is important within causal inference.

A comparison of evidential networks and compositional models

Jiřina Vejnarová (2014)

Kybernetika

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Several counterparts of Bayesian networks based on different paradigms have been proposed in evidence theory. Nevertheless, none of them is completely satisfactory. In this paper we will present a new one, based on a recently introduced concept of conditional independence. We define a conditioning rule for variables, and the relationship between conditional independence and irrelevance is studied with the aim of constructing a Bayesian-network-like model. Then, through a simple example,...

On inhomogeneous Diophantine approximation and the Nishioka-Shiokawa-Tamura algorithm

Takao Komatsu (1998)

Acta Arithmetica

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We obtain the values concerning ( θ , ϕ ) = l i m i n f | q | → ∞ | q | ‖ q θ - ϕ ‖ using the algorithm by Nishioka, Shiokawa and Tamura. In application, we give the values (θ,1/2), (θ,1/a), (θ,1/√(ab(ab+4))) and so on when θ = (√(ab(ab+4)) - ab)/(2a) = [0;a,b,a,b,...].