基于量子粒子群优化算法的光纤光栅参数重构

提出了一种基于量子粒子群优化算法的光纤光栅参数重构方法。该方法通过传输矩阵法得到优化目标函数,并将待优化的光纤光栅参数以粒子表示,再让粒子在解空间模拟量子行为进行搜索。以均匀布拉格光栅和线性啁啾光纤光栅为例,分别采用遗传算法(GA)、经典粒子群优化(PSO)算法以及量子粒子群优化(QPSO)算法对其进行参数重构。与传统粒子群算法及遗传算法相比,该方法借鉴了量子行为,具有更好的收敛性能和稳态性能。数值结果表明,种群规模为40时,针对均匀和非均匀光栅分别进化100代和200代得到的重构参数误差均小于0.5%。     

基于粒子群算法的FBG峰值波长检测技术

提出了一种新的光纤布拉格光栅(FBG)峰值波长检测技术,将改进粒子群算法(PSO)与峰值波长检测技术相结合,应用于在光纤光栅传感网络的波长检测,解决了传统波峰检测技术要求光纤光栅传感器带宽不能重叠和最小位移波形检测计算速度慢的问题.仿真计算结果证明,即使相邻两个FBG传感器的波峰相互叠加时,运用这种方法仍能取得较高的检测精度.     

FBG非均匀应变分布的动态粒子群算法重构研究

基于动态粒子群算法(DPSO)和传输矩阵法,提出了一种新的光纤布喇格光栅(FBG)轴向非均匀应变分布重构方法.利用光栅轴向采样点处的应变值作为粒子,让其在解空间中模拟鸟群行为进行搜索,算法的惯性权重ω根据不同粒子与当前种群中全局最优粒子距离的大小进行动态调整,加快了算法收敛到最优点的速度.采用DPSO对线性、二次、正弦、不连续等4种应变分布形式进行了应变重构,并与量子行为粒子群优化算法(QPSO)的重构结果进行了比较,仿真结果表明,DPSO优化算法可有效地进行光栅轴向菲均匀应变分布的重构,精度和迭代速度较QPSO法有显著提高.     

基于近邻粒子群优化的阵列天线方向图综合

阵列信号处理是近40年来迅速发展的技术,方向图综合的优化是其重要的问题,粒子群优化技术通过简单的算法可以达到很好的方向图综合效果。近邻粒子群优化算法除了利用粒子本身历史最优位置与全体最优位置外,还利用邻居粒子历史最优位置更新本粒子位置,测试函数测试结果表明,这在一定程度上消除了标准粒子群算法容易收敛到局部最优值的缺点。使用这种改进算法的阵列天线的方向图综合也得到了很好的结果     

基于Social Cognition粒子群算法多用户检测

最优多用户检测方法具有最优性能,但复杂度高,利用优化算法求解可以降低实现复杂度。粒子群算法是一种简单有效的新型群智能优化算法,研究了一种Socialcognition模型简化粒子群算法,并应用于大用户量CDMA多用户检测问题,主要考虑降低算法复杂度,提高算法的实现效率。分析及仿真表明该方法在系统用户数量较大时具有较好性能。     

基于重心法的粒子群优化算法

针对函数优化问题,提出了一种基于重心法的粒子群优化算法。该算法利用混沌序列产生粒子的位置和速度,并通过重心法和分类方式更新粒子的速度。最后将算法应用到函数优化问题中,并与其它改进的粒子群算法进行比较。数值结果表明,提高了算法局域搜索能力,全局最优解的精度。     

基于离散粒子群算法的CDMA多用户检测方法

研究了离散粒子群算法，并将其应用于CDMA多用户检测问题，提出一种基于离散粒子群优化算法的CDMA多用户检测的方法。该方法应用一种新的选择和分区搜索的策略，改进搜索的质量和效率。分析以及实验仿真表明该方法具有计算复杂度低且可以得到较好误码率性能的特点，为寻求新的多用户检测方法提供了思路。     

基于混沌粒子群优化的图像相关匹配算法研究

该文将混沌优化搜索技术应用于粒子群优化算法(PSO),提出了一种基于混沌搜索的粒子群优化算法(CPSO),该算法利用了PSO算法的收敛快速性和混沌运动的遍历性、随机性等特点,采用混沌初始化粒子初始位置,在运行过程中根据粒子群适应度的方差来自适应混沌更新粒子位置。几种典型函数的测试结果表明:CPSO提高了对多维空间的全局搜索能力,并可以有效避免早熟现象。将该方法用于图像相关匹配算法,提出了一种新的基于CPSO的图像相关匹配算法。实验结果证明该方法对解决噪声情况下的图像匹配问题十分有效。     

基于混沌粒子群优化的图像相关匹配算法研究

该文将混沌优化搜索技术应用于粒子群优化算法（PSO）,提出了一种基于混沌搜索的粒子群优化算法（CPSO）,该算法利用了PSO算法的收敛快速性和混沌运动的遍历性、随机性等特点,采用混沌初始化粒子初始位置,在运行过程中根据粒子群适应度的方差来自适应混沌更新粒子位置。几种典型函数的测试结果表明：CPSO提高了对多维空间的全局搜索能力,并可以有效避免早熟现象。将该方法用于图像相关匹配算法,提出了一种新的基于CPSO的图像相关匹配算法。实验结果证明该方法对解决噪声情况下的图像匹配问题十分有效。     

基于粒子群算法的阵列波束宽零陷优化设计

作为一种新型的群智能随机优化算法,粒子群优化（PSO ）算法在解决各种非线性复杂问题上得到了广泛的应用。研究了粒子群优化算法在阵列天线方向图零陷加宽技术上的应用,通过实例表明粒子群算法能够在较宽的角度区间上形成满足要求的零陷,在抗干扰应用方面具有较高的应用前景。     

A genetic algorithm for the inverse problem in synthesis of fibergratings

A new method for synthesis of fiber gratings with advanced characteristics is proposed. By combining the Runge-Kutta method for calculating the reflection spectrum of a fiber grating and a genetic algorithm, we obtain a promising method for the synthesis. Compared to other methods, the proposed method facilitates the task of weighting the different requirements to the filter spectrum. In addition, the method is general, and would thus be useful for other inverse problems     

An efficient inverse scattering algorithm for the design ofnonuniform fiber Bragg gratings

Presents an efficient method for the design of complex fiber Bragg gratings. The method relies on the synthesis of the impulse response of the grating by means of a differential layer-peeling algorithm. The algorithm developed takes into account all the multiple reflections inside the grating, giving an exact solution to the inverse scattering problem. Its low algorithmic complexity enables the synthesis of long fiber gratings. The method is illustrated by designing several filters with interest for optical fiber communication systems: dispersionless bandpass filters and second- and third order dispersion compensators     

Novel algorithm for synthesis of fiber gratings

A novel algorithm for the synthesis of fiber gratings is presented.For the first time we propose an effective optimal approach to construct a coupling coefficient function by employing 4th-order Runge-Kutta (R-K) analysis method for calculating the reflection spectra of fiber gratings.The numerical results show that with this proposed method, some required optical filters have been yielded with better features compared with other methods such as Gel'Fand-Levitan-Marchenko (GLM) algorithm.In addition, the performance of different interpolation functions particularly utilized in our algorithm, including linear-type, spline-type, and Hermit-type, are discussed in detail.     

Synthesis method based on genetic algorithm for designing EDFA gain flattening LPFGs having phase-shifted effect

We propose a new synthesis method based on the genetic algorithm for the design of erbium-doped fiber amplifier gain flattening filters. Our genetic algorithm iterates starting with the long period fiber gratings structure constructed by inserting the phase-shifted long period fiber gratings in the middle of the structure, for the more accurately matched spectrum to the desired erbium-doped fiber amplifier gain flattening filter. To verify a synthesizing technique using the proposed algorithm, we have synthesized the long period fiber gratings structures according to the inverted gain spectrum of a commercially available erbium-doped fiber amplifier over the entire 1525–1570 nm range, theoretically. We have also obtained the synthesized structure was more accurate than the structure without phase-shifted section.     

一种重构多信道布拉格光栅的混杂算法

由于光纤光敏性的限制,当信道数N变得很大时,采用幅度取样方式制作多信道光栅将变得非常困难.通过相位取样来制作多信道光栅被证明是一种能有效降低峰值折变量的方法.提出一种采用逆散射技术和优化策略的混杂算法有效地设计多信道光栅.由遗传算法进行优化,得到每一个信道相应的相位因子的最优值,改进了多信道光栅复杂的反射谱.再由Layer-peeling算法为依据引入了相位因子后的频谱响应重构光栅.通过对信道间相对相位的优化,制作这种多信道光栅所需的峰值折变量降低为单信道光栅的√N倍.经过数值仿真,得到8信道光栅的峰值折变量大约为单信道光栅的√8倍.     

用遗传算法从时延特性重构光纤光栅参数

提出了采用遗传算法(GA)结合传输矩阵法从需要的时延特性对光纤光栅进行参数重构的方法。该方法以时延为目标函数,由光纤光栅参数,包括光栅长度、折射率调制、光栅周期和光栅啁啾,组成种群中的待优化的个体,经过若干代遗传得到最优结果。用实值编码遗传算法实现了对均匀光纤光栅、啁啾光纤光栅和切趾啁啾光纤光栅参数的重构。数值仿真结果表明该方法对光纤光栅的时延特性参数重构十分有效。由斜率为100ps/nm,最大时延为300ps,中心波长为1555.2nm的理想线性时延特性重构出切趾啁啾光纤光栅的参数。此方法可以有效地从时延信息中提取光纤光栅参数,能够应用在利用光纤光栅时延特性的光控相控阵天线设计中。     

Phase reconstruction from reflectivity in fiber Bragg gratings

We propose a method for phase, time delay, and impulse response reconstruction from the spectral power reflectance or reflectivity in fiber Bragg gratings (FBGs). This method is based on causality and stability conditions and uses the Hilbert and Wiener-Lee transforms. In order to obtain a complete study of the algorithm, we have applied it to uniform and nonuniform fiber Bragg gratings. Finally, we get a complete characterization of a experimental uniform fiber Bragg grating, from the measured reflectivity, by means of the phase reconstruction algorithm. Results show a good agreement between exact and reconstructed functions     

Iterative solution to the Gel'Fand-Levitan-Marchenko coupledequations and application to synthesis of fiber gratings

In this paper, we develop an iterative solution to the coupled Gel'Fand-Levitan-Marchenko integral equations. It will be proved that this new technique outstands other methods such as the exact GLM solution or the Fourier method. As one of its many applications, the synthesis of fiber gratings for dispersion equalization will be tackled     

使用PSO算法的二阶偏振模色散自适应补偿实验

偏振模色散（PMD）已经成为高速光纤通信系统发展的严重障碍。我们将粒子群优化（Particle Swarm Optimization—PSO）算法作为偏振模色散自适应补偿中的反馈控制算法，对光链路中的PMD信号进行收索跟踪，并控制偏振控制器（Polarization Controller—PC），成功的实现了对二阶PMD的自适应补偿。实验结果表明，粒子群优化算法能够避免陷入局部极值而快速的搜索全局最佳值，同时它还具有很强的抗链路噪声的能力，补偿效果良好。     

Calculation of the Figure of Merit of Linearly Chirped Fiber Gratings for Dispersion Compensation

1IntroductionBecauseoftheadventoferbium-dopedamplifiers,thelengthoftheophcalfiberlinksisnolongerlicitedbytheabsorphon,butratherbythechromaticdispersionofthefiber.Especially'theophcalsignalshapeissoseriouslydestroyedthatthebit-error-rate(BER)isratherhigherinthelonghaulhigh-bit-rateophcalcommunicationsystem.Sothedispersionoffibermustbecompensatedbyvariouskindsofdevices.Amongthem,thecompensatorusingthelinearlychirpedfibergratingshascausedagreatinterestindispersioncompensatingdeVices11-5].Onemus…