Pre-processing inputs for optimally-configured time-delay neural networks
Taskaya-Temizel, T, Casey, MC and Ahmad, K (2005) Pre-processing inputs for optimally-configured time-delay neural networks Electronics Letters, 41 (4). 198 - 200. ISSN 0013-5194
Pre-print.pdf - Accepted Version
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A procedure for pre-processing non-stationary time series is proposed for modelling with a time-delay neural network (TDNN). The procedure stabilises the mean of the series and uses a fast Fourier transform to determine the TDNN input size. Results of applying this procedure on five well-known data sets are compared with existing hybrid neural network techniques, demonstrating improved prediction performance.
|Uncontrolled Keywords:||SERIES, ARIMA, MODEL|
|Divisions:||Faculty of Engineering and Physical Sciences > Computing Science|
|Depositing User:||Symplectic Elements|
|Date Deposited:||22 Jun 2011 12:48|
|Last Modified:||08 Nov 2013 12:08|
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