Results 211 to 220 of about 15,646 (263)
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Neural Networks, 1995
Abstract We consider neural units whose response functions are Lorentzians rather than the usual sigmoids or steps. This consideration is justified by the fact that neurons can be paired and that a suitable difference of the sigmoids of the paired neurons can create a window response function. Lorentzians are special cases of such windows and we take
Bertrand Giraud +3 more
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Abstract We consider neural units whose response functions are Lorentzians rather than the usual sigmoids or steps. This consideration is justified by the fact that neurons can be paired and that a suitable difference of the sigmoids of the paired neurons can create a window response function. Lorentzians are special cases of such windows and we take
Bertrand Giraud +3 more
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Parallel Algorithms and Applications, 1997
This paper examines the structure of artificial neural networks (ANN) and the operation of their algorithms in order to identify the forms of parallelism that may be inherent in them. Parallelism within the topological structure of ANNs are seen to be of two forms: neuron and synapse.
David Al-Dabass +2 more
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This paper examines the structure of artificial neural networks (ANN) and the operation of their algorithms in order to identify the forms of parallelism that may be inherent in them. Parallelism within the topological structure of ANNs are seen to be of two forms: neuron and synapse.
David Al-Dabass +2 more
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International Journal of Intelligent Systems, 1994
We suggest a description of thermodynamical systems, focusing on near-to-equilibrium states of the systems, within the structure of random graphs to map them to neural nets. We then use the component subgraph configurations of the random graphs that are the stationary states of the near-to-equilibrium systems to represent concepts in an unstructured ...
Khalid Md. Nor +4 more
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We suggest a description of thermodynamical systems, focusing on near-to-equilibrium states of the systems, within the structure of random graphs to map them to neural nets. We then use the component subgraph configurations of the random graphs that are the stationary states of the near-to-equilibrium systems to represent concepts in an unstructured ...
Khalid Md. Nor +4 more
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Biosystems, 1967
Abstract A mathematical apparatus is developed that deals with networks of elements which are connected to each other by well defined connection rules and which perform well defined operations on their inputs. The output of these elements either is transmitted to other elements in the network or — should they be terminal elements — represents the ...
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Abstract A mathematical apparatus is developed that deals with networks of elements which are connected to each other by well defined connection rules and which perform well defined operations on their inputs. The output of these elements either is transmitted to other elements in the network or — should they be terminal elements — represents the ...
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1995
Although the issue of reliability is extensively discussed in the software engineering literature, it has received only limited attention in the Neural Computing community. In this paper, the software engineering concept of diversity is made use of to improve the performance of a neural net system solution to a problem of fault diagnosis in a marine ...
Amanda J. C. Sharkey +2 more
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Although the issue of reliability is extensively discussed in the software engineering literature, it has received only limited attention in the Neural Computing community. In this paper, the software engineering concept of diversity is made use of to improve the performance of a neural net system solution to a problem of fault diagnosis in a marine ...
Amanda J. C. Sharkey +2 more
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Neural Networks, 2001
Formulations of artificial neural networks are directly related to assumptions about neural coding in the brain. Traditional connectionist networks assume channel-based rate coding, while time-delay networks convert temporally-coded inputs into rate-coded outputs.
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Formulations of artificial neural networks are directly related to assumptions about neural coding in the brain. Traditional connectionist networks assume channel-based rate coding, while time-delay networks convert temporally-coded inputs into rate-coded outputs.
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Communications of the ACM, 2019
Yoshua Bengio, Geoffrey Hinton, and Yann LeCun this month will receive the 2018 ACM A.M. Turing Award for conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing.
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Yoshua Bengio, Geoffrey Hinton, and Yann LeCun this month will receive the 2018 ACM A.M. Turing Award for conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing.
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1998
Abstract On first thought, modeling networks of neurons would seem to be an enterprise having little in common with modeling a checkersplayer. My own first reaction to Art Samuel’s checkersplayer, as I mentioned earlier, was to think the ideas fascinating but far removed from the study of neural networks.
James J. Buckley, Thomas Feuring
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Abstract On first thought, modeling networks of neurons would seem to be an enterprise having little in common with modeling a checkersplayer. My own first reaction to Art Samuel’s checkersplayer, as I mentioned earlier, was to think the ideas fascinating but far removed from the study of neural networks.
James J. Buckley, Thomas Feuring
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2007 IEEE Symposium on Foundations of Computational Intelligence, 2007
We analyze a bivariate marginal distribution genetic model in case of infinite populations and provide relations between the associated infinite population genetic system and the neural networks. A lower bound on population size is exhibited stating that the behaviour of the finite population system, in case of sufficiently large sizes, can be suitably
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We analyze a bivariate marginal distribution genetic model in case of infinite populations and provide relations between the associated infinite population genetic system and the neural networks. A lower bound on population size is exhibited stating that the behaviour of the finite population system, in case of sufficiently large sizes, can be suitably
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The Bulletin of Mathematical Biophysics, 1948
The structure of a complete or incomplete neural net is represented here by several matrices. The activity equation of the net follows in a general form. A chain or cycle is defined as a neural structure whose connection matrix is unitary. We can compute the number of simple chains by a recurrent formula.
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The structure of a complete or incomplete neural net is represented here by several matrices. The activity equation of the net follows in a general form. A chain or cycle is defined as a neural structure whose connection matrix is unitary. We can compute the number of simple chains by a recurrent formula.
openaire +2 more sources