Results 231 to 240 of about 27,097 (268)

The complex backpropagation algorithm

IEEE Transactions on Signal Processing, 1991
The backpropagation (BP) algorithm that provides a popular method for the design of a multilayer neural network to include complex coefficients and complex signals so that it can be applied to general radar signal processing and communications problems. It is shown that the network can classify complex signals. The generalization of the BP to deal with
Henry Leung, Simon Haykin 0001
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Out-of-core backpropagation

1990 IJCNN International Joint Conference on Neural Networks, 1990
Backpropagation learning can execute at supercomputer speed from training data sets of unprecedented size when supercomputer main memory is backed with newly available parallel arrays of commodity disk drives. An efficient implementation of backpropagation learning was modified and extended to iterate through training data sets stored on a parallel ...
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Adaptability of the backpropagation procedure

IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339), 2003
Possible paradigms for concept learning by feedforward neural networks include discrimination and recognition. An interesting aspect of this dichotomy is that the recognition-based implementation can learn certain domains much more efficiently than the discrimination-based one, despite the close structural relationship between the two systems.
Nathalie Japkowicz, Stephen Jose Hanson
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A fuzzy backpropagation algorithm

Fuzzy Sets and Systems, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Stefka Stoeva, Alexander Nikov
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Backpropagation

2023
Christopher M. Bishop, Hugh Bishop
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Strictly local backpropagation

1990 IJCNN International Joint Conference on Neural Networks, 1990
In conventional implementations of the backpropagation method, the delta error terms which propagate the error back through the network are global (common) variables shared by multiple nodes. A modified implementation of the algorithm which permits this process to occur using only local values of all variables is presented.
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Backpropagation

2022
Robert H. Chen, Chelsea Chen
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From Backpropagation to Neurocontrol

2011
This chapter provides an overview of the most powerful practical tools developed so far, and under development, in the areas which the Engineering Directorate of National Science Foundation has called “cognitive optimization and prediction”. It deals with a condensed overview of key tools and discusses the historical background and the larger ...
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Backpropagation through time: what it does and how to do it

Proceedings of the IEEE, 1990
P J Werbos
exaly  

Generalization of backpropagation with application to a recurrent gas market model

Neural Networks, 1988
Paul Werbos
exaly