University of Surrey

Test tubes in the lab Research in the ATI Dance Research

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

[img]
Preview
PDF
Pre-print.pdf - Accepted Version
Available under License : See the attached licence file.

Download (67kB)
[img] Plain Text (licence)
licence.txt

Download (1kB)

Abstract

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.

Item Type: Article
Uncontrolled Keywords: SERIES, ARIMA, MODEL
Related URLs:
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
URI: http://epubs.surrey.ac.uk/id/eprint/3024

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year


Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800