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Instantaneously trained neural networks

Instantaneously trained neural networks are feedforward artificial neural networks that create a new hidden neuron node for each novel training… Expand
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2019
2019
Abstract Automatic lung disease detection is a critical challenging task for researchers because of the noise signals getting… Expand
Highly Cited
2013
Highly Cited
2013
We have performed direct numerical simulation of turbulent open channel flow over a smooth horizontal wall in the presence of… Expand
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Review
2006
Review
2006
This paper presents a review of instantaneously trained neural networks (ITNNs). These networks trade learning time for size and… Expand
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2006
2006
Neural network architectures such as backpropagation networks, perceptrons or generalized Hopfield networks can handle complex… Expand
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2005
2005
SummaryThe influence of temperature in the range 25° to 45°C on the rate of dissolution and the equilibrium concentration of… Expand
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2003
2003
Multiplexing and space-time coding are competing ways of extracting capacity out of MIMO wireless systems. We address the problem… Expand
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2002
2002
  • S. Kak
  • Inf. Sci.
  • 2002
  • Corpus ID: 1860225
This paper presents FC networks which are instantaneously trained neural networks that allow rapid learning of non-binary data… Expand
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Highly Cited
2001
Highly Cited
2001
The possible responses of ecosystem processes to rising atmospheric CO2 concentration and climate change are illustrated using… Expand
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1999
1999
methods—such as the backpropa-gation algorithm or self-organizing maps, the standard techniques for generaliza-tion—are… Expand
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Highly Cited
1987
Highly Cited
1987
One option-pricing problem which has hitherto been unsolved is the pricing of European call on an asset which has a stochastic… Expand
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