Pre-processing inputs for optimally-configured time-delay neural networks

Date

2005-02-01

Author

Taşkaya Temizel, Tuğba
Casey, MC
Ahmad, K

Metadata

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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

Citation Formats

T. Taşkaya Temizel, M. Casey, and K. Ahmad, “Pre-processing inputs for optimally-configured time-delay neural networks,” ELECTRONICS LETTERS, vol. 41, no. 4, pp. 198–200, 2005, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/70043.