Results 131 to 140 of about 122,388 (186)
Some of the next articles are maybe not open access.
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. The previous chapter established
James J. Buckley, Thomas Feuring
openaire +2 more sources
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. The previous chapter established
James J. Buckley, Thomas Feuring
openaire +2 more sources
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 ...
openaire +2 more sources
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 ...
openaire +2 more sources
IEEE Transactions on Neural Networks, 1991
Application of neural nets to invariant pattern recognition is considered. The authors study various techniques for obtaining this invariance with neural net classifiers and identify the invariant-feature technique as the most suitable for current neural classifiers.
E, Barnard, D, Casasent
openaire +2 more sources
Application of neural nets to invariant pattern recognition is considered. The authors study various techniques for obtaining this invariance with neural net classifiers and identify the invariant-feature technique as the most suitable for current neural classifiers.
E, Barnard, D, Casasent
openaire +2 more sources
American Political Science Review, 2004
Beck, King, and Zeng (2000) offer both a sweeping critique of the quantitative security studies field and a bold new direction for future research. Despite important strengths in their work, we take issue with three aspects of their research: (1) the substance of the logit model they compare to their neural network, (2) the standards they use for ...
SCOTT DE MARCHI +2 more
openaire +1 more source
Beck, King, and Zeng (2000) offer both a sweeping critique of the quantitative security studies field and a bold new direction for future research. Despite important strengths in their work, we take issue with three aspects of their research: (1) the substance of the logit model they compare to their neural network, (2) the standards they use for ...
SCOTT DE MARCHI +2 more
openaire +1 more source
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
B.G. Giraud +3 more
openaire +1 more source
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
B.G. Giraud +3 more
openaire +1 more source
Science, 1998
I would like to clarify some features of the program NeuroShell Easy described in “Neural nets for novices” by John Wass ( Science 's Compass, 7 Aug., p. 789). First, our Turboprop2 paradigm is not based on the General Regression Neural Network (GRNN), although GRNN is also in the package. Second, the software is not just for novices.
openaire +1 more source
I would like to clarify some features of the program NeuroShell Easy described in “Neural nets for novices” by John Wass ( Science 's Compass, 7 Aug., p. 789). First, our Turboprop2 paradigm is not based on the General Regression Neural Network (GRNN), although GRNN is also in the package. Second, the software is not just for novices.
openaire +1 more source
Adaptive-clustering optical neural net
Applied Optics, 1990Pattern recognition techniques (for clustering and linear discriminant function selection) are combined with neural net methods (that provide an automated method to combine linear discriminant functions into piecewise linear discriminant surfaces).
D P, Casasent, E, Barnard
openaire +2 more sources
Engineering Multiversion Neural-Net Systems
Neural Computation, 1996In this paper we address the problem of constructing reliable neural-net implementations, given the assumption that any particular implementation will not be totally correct. The approach taken in this paper is to organize the inevitable errors so as to minimize their impact in the context of a multiversion system, i.e., the system functionality is ...
D, Partridge, W B, Yates
openaire +2 more sources
2017
When problems are complex and cannot be solved through conventional methods such as statistical or management science models, and when human expertise is not sufficient for efficiently finding high-quality solutions, we can consider the use of machine learning techniques.
Brian R. Huguenard, Deborah J. Ballou
openaire +1 more source
When problems are complex and cannot be solved through conventional methods such as statistical or management science models, and when human expertise is not sufficient for efficiently finding high-quality solutions, we can consider the use of machine learning techniques.
Brian R. Huguenard, Deborah J. Ballou
openaire +1 more source
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 ...
Nor, Khalid Md. +4 more
openaire +1 more source
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 ...
Nor, Khalid Md. +4 more
openaire +1 more source