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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

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Official URL: http://dx.doi.org/10.1049/el:20058016

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
Divisions:Faculty of Engineering and Physical Sciences > Computing Science
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ID Code:3024
Deposited By:Symplectic Elements
Deposited On:22 Jun 2011 13:48
Last Modified:16 Feb 2013 16:04

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