Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/9900
Title: Compression of ultraviolet-visible spectrum with recurrent neural network
Authors: Li, LK
Chau, FT
Leung, AKM
Keywords: Recurrent neural network
Spectral compression
Ultraviolet-visible spectrum
Issue Date: 2000
Publisher: Elsevier Science Bv
Source: Chemometrics and intelligent laboratory systems, 2000, v. 52, no. 2, p. 135-143 How to cite?
Journal: Chemometrics and Intelligent Laboratory Systems 
Abstract: Data compression method based on the recurrent neural network (RNN) of the dynamical system approach was proposed and applied to ultraviolet-visible (UV-VIS) spectra. RNN schemes with different network size were studied and their performance was evaluated by using both synthetic and experimental data. It was found that the storage space of the spectral information under study could be reduced significantly by using the proposed RNN method with quality spectra regenerated from the compressed data. Furthermore, the method was found to perform as good as the wavelet transform (WT) in data compression and in some cases, even better.
URI: http://hdl.handle.net/10397/9900
ISSN: 0169-7439
DOI: 10.1016/S0169-7439(00)00074-5
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