Multiple channel crosstalk removal using limited connectivity neural networks

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Multiple channel crosstalk removal using limited connectivity neural networks

Limited connectivity neural network architectures are investigated for the removal of crosstalk in systems using mutually overlapping sub-channels for the communication of multiple signals, either analogue or digital. The crosstalk error is modelled such that a fixed proportion of the signals in adj...

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Bibliographic Details
Main Authors:	Craven, Michael P., Curtis, K. Mervyn, Hayes-Gill, Barrie R.
Format:	Conference or Workshop Item
Published:	1996
Subjects:	neural networks ANN cross-talk gradient descent learning
Online Access:	https://eprints.nottingham.ac.uk/1903/

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