Results 211 to 220 of about 609,020 (244)
Some of the next articles are maybe not open access.
2009
Neural networks are a class of intelligent learning machines establishing the relationships between descriptors of real-world objects. As optimisation tools they are also a class of computational algorithms implemented using statistical/numerical techniques for parameter estimate, model selection, and generalisation enhancement.
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Neural networks are a class of intelligent learning machines establishing the relationships between descriptors of real-world objects. As optimisation tools they are also a class of computational algorithms implemented using statistical/numerical techniques for parameter estimate, model selection, and generalisation enhancement.
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Physical Review E, 1993
We propose a class of network models suited for negative-choice classification.
, Nowak, , Lewenstein, , Tarkowski
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We propose a class of network models suited for negative-choice classification.
, Nowak, , Lewenstein, , Tarkowski
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2007
Some of the (comparatively older) numerical results on neural network models obtained by our group are reviewed. These models incorporate synaptic connections constructed by using the Hebb's rule. The dynamics is determined by the internal field which has a weighted contribution from the time delayed signals.
Bikas K, Chakrabarti, Abhik, Basu
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Some of the (comparatively older) numerical results on neural network models obtained by our group are reviewed. These models incorporate synaptic connections constructed by using the Hebb's rule. The dynamics is determined by the internal field which has a weighted contribution from the time delayed signals.
Bikas K, Chakrabarti, Abhik, Basu
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Annual Review of Physiology, 1985
Despite the fact that a large number of neuronal oscillators have been described, there are only a few good examples that illustrate how they operate at the cellular level. For most, there is some isolated information about different aspects of the oscillator network, but too little to explain the whole mechanism.
A I, Selverston, M, Moulins
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Despite the fact that a large number of neuronal oscillators have been described, there are only a few good examples that illustrate how they operate at the cellular level. For most, there is some isolated information about different aspects of the oscillator network, but too little to explain the whole mechanism.
A I, Selverston, M, Moulins
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2021
In this section, we will see how to train a neural network model in the Wolfram Language, how to access the results, and the trained network. We will review the basic commands to export and import a net model. We end the chapter with the exploration of the Wolfram Neural Net Repository and the review of the LeNet network model.
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In this section, we will see how to train a neural network model in the Wolfram Language, how to access the results, and the trained network. We will review the basic commands to export and import a net model. We end the chapter with the exploration of the Wolfram Neural Net Repository and the review of the LeNet network model.
openaire +1 more source