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). pp. 198-200.
Pre-print.pdf - Accepted version Manuscript
Available under License : See the attached licence file.
Plain Text (licence)
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.
|Divisions :||Faculty of Engineering and Physical Sciences > Computing Science|
|Date :||17 February 2005|
|Identification Number :||https://doi.org/10.1049/el:20058016|
|Uncontrolled Keywords :||SERIES, ARIMA, MODEL|
|Related URLs :|
|Depositing User :||Symplectic Elements|
|Date Deposited :||22 Jun 2011 12:48|
|Last Modified :||08 Nov 2013 12:08|
Actions (login required)
Downloads per month over past year