We apply an adaptive feedback loop to control a ultra-violet (UV) femtosecond pulse shaping apparatus. The adaptive feedback control is implemented by a continuous parameter.genetic algorithm. We use the adaptive shap...
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We apply an adaptive feedback loop to control a ultra-violet (UV) femtosecond pulse shaping apparatus. The adaptive feedback control is implemented by a continuous parameter.genetic algorithm. We use the adaptive shaper to compensate for the pulse chirp. The.genetic algorithm produces a pulse with a width of 115 fs, identical to that of the transformlimited pulse. We then apply the adaptive shaper to the Stokes pulse in a femtosecond coherent anti-Stokes Raman scattering (CARS) experiment on dipicolinic acid solution. The algorithm maximizes the first CARS beat signal at the probe pulse delay of 650 fs. We confirm that a transformlimited Stokes pulse achieves the best detection sensitivity. (c) 2006 Optical Society of America
This paper explores the feasibility of microwave imaging a buried object by the GA and using the S-11 parameter of a radiation antenna rather than data of the scattered electromagnetic field. To improve the efficiency...
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This paper explores the feasibility of microwave imaging a buried object by the GA and using the S-11 parameter of a radiation antenna rather than data of the scattered electromagnetic field. To improve the efficiency of the GA-based algorithm, a technique of limiting the location of the buried object prior to the implement of the GA is proposed, and the GA is parallelized and executed on a PC cluster. A few numerical examples are presented, in which the dimension and location of a 3-D object buried in the earth are recovered. Results validate the proposed GA-based microwave imaging algorithm.
A novel design approach for erbium-doped fiber amplifiers is proposed based on particle swarm optimization algorithm. The main six parameters of the EDFAs including: pumping wavelength, input signal power, fiber numer...
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A novel design approach for erbium-doped fiber amplifiers is proposed based on particle swarm optimization algorithm. The main six parameters of the EDFAs including: pumping wavelength, input signal power, fiber numerical aperture, erbium-doped area radius, erbium concentration, and the fiber length are optimized utilizing a fast and efficient method called particle swarm optimization algorithm. In this paper, a combination of fiber amplifier bandwidth, gain, and flatness are taken into account as objective function and the results are presented for different pump powers. Our investigation shows that particle swarm optimization algorithm outperforms.genetic algorithm in convergence speed, straightforwardness, and coping with highdimensional spaces, when the parameters of EDFA are to be optimized. It has been shown that the required time for the optimization of the fiber amplifier parameters is reduced four times by using particle swarm optimization algorithm, compared to.genetic algorithm method.
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