Neural network system identification of chaotic optical systems with the chaos speedup BP algorithm

An algorithm for quickly training the BP neural network system identifier (BPNNSI) of the chaotic optical systems is presented in this paper. The ability of this algorithm, termed as the chaos speedup BP algorithm (CSBPA), has been demonstrated with the computer simulation of identifying the Bragg diffraction acousto-optic system (BDAOS) in which a 1:4:1 BP network was employed in identification. Taking the normalized output time series of the BDAOS as the training series, the BPNNSI was trained with the CSBPA as follows: (1) trained the BPNNSI to learn a chaotic state of the BDAOS with the BP algorithm where the initial weight distribution was set randomly; (2) took the final weight distribution obtained in (1) as the initial weight distribution for the other states of the BDAOS to be identified; (3) trained the BPNNSI to learn the other states still with the BP algorithm but with the initial weight distribution obtained in (2).© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.