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Pre-processing inputs for optimally-configured time-delay neural networks
Date
2005-02-01
Author
Taşkaya Temizel, Tuğba
Ahmad, K
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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.
Subject Keywords
Electrical and Electronic Engineering
URI
https://hdl.handle.net/11511/70043
Journal
ELECTRONICS LETTERS
DOI
https://doi.org/10.1049/el:20058016
Collections
Graduate School of Informatics, Article
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T. Taşkaya Temizel and K. Ahmad, “Pre-processing inputs for optimally-configured time-delay neural networks,”
ELECTRONICS LETTERS
, pp. 198–200, 2005, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/70043.