Title :
Design of optimal length low-dispersion FBG filter using covariance matrix adapted evolution
Author :
Baskar, S. ; Alphones, A. ; Suganthan, P.N. ; Ngo, N.Q. ; Zheng, R.T.
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
Abstract :
The design of a low-dispersion fiber Bragg grating (FBG) with an optimal grating length using covariance matrix adapted evolution strategy (CMAES) is presented. A novel objective function formulation is proposed for the optimal grating length low-dispersion FBG design. The CMAES algorithm employs adaptive learning procedure to identify correlations among the design parameters. The design of a low-dispersion FBG filter with 25-GHz (or 0.2 nm in the 1550-nm band) bandwidth is considered. Simulation results, obtained using the codes available in public domain (the codes are available from the third author), show that the CMAES algorithm is more appropriate for the practical design of length optimized FBG-based filters when compared with the other optimization methods.
Keywords :
Bragg gratings; covariance matrices; learning (artificial intelligence); optical design techniques; optical fibre dispersion; optical fibre filters; optimisation; physics computing; 1550 nm; 25 GHz; CMAES algorithm; FBG filter; adaptive learning; correlation identification; covariance matrix adapted evolution; fiber Bragg grating; low-dispersion FBG design; objective function formulation; optimal grating length; optimal length FBG design; optimization methods; Algorithm design and analysis; Bandwidth; Bragg gratings; Covariance matrix; Design optimization; Fabrication; Fiber gratings; Filters; Inverse problems; Optimization methods; Covariance matrix adapted evolution strategy (CMAES); fiber Bragg grating (FBG); filter design; genetic algorithms (GAs); low-dispersion; optimal grating length;
Journal_Title :
Photonics Technology Letters, IEEE
DOI :
10.1109/LPT.2005.854350
