Harris, C.J. and Brown, M.
Neurofuzzy networks for online modelling and control with provable learning and stability conditions
At Int. Conf. on Systems, Man, and Cybernetics.
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This paper considers a wide class of basis associative memory networks and their learning and network conditioning for online modelling and control. It is shown that the networks parameter convergence rate, stability and gradient noise all depend upon the condition number C(R) of the basis function autocorrelation function R. This analysis shows that for online modelling networks should be locally generalising and have condition number tending to unity.
Conference or Workshop Item
||Organisation: IEEE Address: San Antonio, Texas
|Venue - Dates:
||Int. Conf. on Systems, Man, and Cybernetics, 1994-01-01
||Southampton Wireless Group
||04 May 1999
||18 Apr 2017 00:23
|Further Information:||Google Scholar|
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