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Displaying similar documents to “Erlang distributed activity times in stochastic activity networks”

Prognosis and optimization of homogeneous Markov message handling networks

Pavel Boček, Tomáš Feglar, Martin Janžura, Igor Vajda (2001)

Kybernetika

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Message handling systems with finitely many servers are mathematically described as homogeneous Markov networks. For hierarchic networks is found a recursive algorithm evaluating after finitely many steps all steady state parameters. Applications to optimization of the system design and management are discussed, as well as a program product 5P (Program for Prognosis of Performance Parameters and Problems) based on the presented theoretical conclusions. The theoretic achievements as well...

On the outstanding elements and record values in the exponential and gamma populations.

G. S. Lingappaiah (1981)

Trabajos de Estadística e Investigación Operativa

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Outstanding elements and recorded values are discussed in this paper as related to exponential and gamma populations. First, the problem of prediction is considered when there are available, k sets of independent observations from a general-type exponential distribution. In such a case, prediction of the n-th record value in the k-th set is made in terms of n-th (i = 1, ..., k-1) record values from other (k-1) sets. For this purpose a predictive distribution is obtained. Secondly, the...

A new approach to image reconstruction from projections using a recurrent neural network

Robert Cierniak (2008)

International Journal of Applied Mathematics and Computer Science

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A new neural network approach to image reconstruction from projections considering the parallel geometry of the scanner is presented. To solve this key problem in computed tomography, a special recurrent neural network is proposed. The reconstruction process is performed during the minimization of the energy function in this network. The performed computer simulations show that the neural network reconstruction algorithm designed to work in this way outperforms conventional methods in...

Determining the weights of a Fourier series neural network on the basis of the multidimensional discrete Fourier transform

Krzysztof Halawa (2008)

International Journal of Applied Mathematics and Computer Science

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This paper presents a method for training a Fourier series neural network on the basis of the multidimensional discrete Fourier transform. The proposed method is characterized by low computational complexity. The article shows how the method can be used for modelling dynamic systems.

The logic of neural networks.

Juan Luis Castro, Enric Trillas (1998)

Mathware and Soft Computing

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This paper establishes the equivalence between multilayer feedforward networks and linear combinations of Lukasiewicz propositions. In this sense, multilayer forward networks have a logic interpretation, which should permit to apply logical techniques in the neural networks framework.