Shooting algorithm and particle swarm optimization based Raman fiber amplifiers gain spectra design

An initial value determination method with a contraction factor for the counter-pumped Raman coupled equations is proposed. This method is used in conjunction with initial guess correction mechanism of Newton's method to construct a new efficient shooting algorithm for the solution of counter-pumped Raman coupled equations. The particle'swarm optimization is used to find the optimal wavelengths and powers for the pumps. By combining the new shooting algorithm and particle swarm optimization a powerful approach to the design of gain spectra for Raman fiber amplifiers is developed. Using this approach a counter-pumped broadband Raman fiber amplifier in C + L-band is designed and optimized. An average on-off gain of 9.3 dB for a bandwidth of 95 nm is obtained using only 4 pumps, with an in-band ripple level of ± 0.7 dB.     

Optimization of pump parameters for gain flattened Raman fiber amplifiers based on artificial fish school algorithm

In this work, a novel metaheuristic named artificial fish school algorithm is introduced into the optimization of pump parameters for the design of gain flattened Raman fiber amplifiers for the first time. Artificial fish school algorithm emulates three simple social behaviors of a fish in a school, namely, preying, swarming and following, to optimize a target function. In this algorithm the pump wavelengths and power levels are mapped respectively to the state of a fish in a school, and the gain of a Raman fiber amplifier is mapped to the concentration of a food source for the fish school to search. Application of this algorithm to the design of a C-band gain flattened Raman fiber amplifier leads to an optimized amplifier that produces a flat gain spectrum with 0.63 dB in band ripple for given conditions. This result demonstrates that the artificial fish school algorithm is efficient for the optimization of pump parameters of gain flattened Raman fiber amplifiers.     

General and effective dynamic gain spectrum control of broadband raman amplifiers with multi-wavelength pumping

An effective feedback algorithm is proposed to dynamically control the gain spectra of multi-wavelength pumped broadband Raman amplifiers. Based on Raman coupling power equations, a simple saturation factor is introduced to achieve the adjusting matrix. By using this method, efficient pump adjustment can be carried out to accomplish wide-range dynamic gain spectrum control (larger than 22 dB dynamic range) as well as automatic gain clamping even for 90 nm bandwidth, highly-saturated RAs. Moreover, this algorithm can be well applied to different fiber types as well as pumping schemes. Some useful guidelines are also demonstrated.     

An effective numerical method for gain profile optimizations of multi pumped fiber Raman amplifiers

In this paper, we have solved propagation equations of multi-pump fiber Raman amplifier using Runge–Kutta (RK 4th order) numerical method and pump power evolutions along with the fiber length. They are used to calculate the net gain and gain ripple by varying the input signals powers for different fiber lengths. The pump powers are optimized by genetic algorithm and resulting net gain and gain ripple are reported graphically as well as in tabular form. The optimum minimum gain ripple is 0.26 dB for 1 mW input signal powers for 50 km fiber length. By increasing the fiber length gain ripple increases to 0.5 dB for 0.1 mW input signal power. In comparison to other methods reported in the literature, our method is simple to implement and efficient for numerical design of Raman amplification in optical communication systems.     

A moment method for analysis the gain spectrum in fiber Raman amplifier with broadband pumps

The governing equations of optical fiber Raman amplifier with broadband pumps in the steady state are systems of uncountable nonlinear ordinary differential equations (NODE). In this paper, the Moment method is used to reduce the uncountable system of NODE to a system of finite number of NODE. This system of equations is solved numerically. The results are compared with that of the full numerical method. It was shown that the Moment method is a precise and efficient technique for analysis of optical fiber Raman amplifier with broadband pumps.     

Multi-channel gain and noise figure evaluation of Raman/EDFA hybrid amplifiers

We present detailed multi-channel experimental characterization of different configurations of single pump hybrid Raman-erbium doped fiber (EDF) amplifiers. The incorporation of an EDF section in a dispersion compensating Raman amplifier is demonstrated to provide superior performance than Raman only system. It is shown that the multi-channel gain spectrum is quite different form the single-channel case. We have also measured the polarization dependent gain (PDG) of the hybrid amplifier configurations and results show that different configurations of hybrid amplifiers have different PDG effects on long-haul optically amplified link.     

多波长抽运宽带光纤拉曼放大器的数值模拟与优化

采用平均功率分析算法对多波长抽运宽带光纤拉曼放大器进行了细致的数值模拟,并根据多抽运拉曼增益谱的特点和不同抽运波长对增益斜率的不同影响提出了一种新的有效的抽运优化算法,并利用这种方法对10波长抽运的光纤拉曼放大器进行了优化,获得了70nm带宽上增益谱波动低于0．5dB的结果。     

光纤喇曼放大器的特性及其在宽带通信中的应用

随着宽带业务的增长和 DWDM技术的发展 ,人们需要更宽增益带宽的全光放大器。光纤喇曼放大器由于其可放大任意波长信号的特性而得到广泛的关注和重视。介绍了喇曼放大器的特性 ,总结了国外近年来对喇曼放大器在宽带通信应用中的研究 ,并讨论了喇曼放大器的发展方向     

双折射色散阶跃光纤中拉曼效应和参量放大增益谱

在拉曼效应和参量放大共同作用下,当激光脉冲在双折射光纤中传输时,根据所遵循的耦合模方程,通过引入平行拉曼增益的洛伦兹模型,导出了当输入泵浦波偏振方向同双折射轴成45°角时,在双折射色散阶跃光纤中拉曼效应和参量放大共同作用所导致的增益,讨论并分析了在不同色散区增益谱随相关参量的变化。结果表明:由于拉曼效应、参量放大、双折射和色散的相互作用,导致增益谱的斯托克斯波与反斯托克斯波彼此不对称;在反常色散区,产生的增益以反斯托克斯波为主,在正常色散区则以斯托克斯波为主;当表征距离的级数m发生变化时,增益谱也随之发生变化,可以利用色散阶跃光纤在适当的级数m位置提取T频率脉冲。     

Application of multi-phase particle swarm optimization technique to inverse radiation problem

The multi-phase particle swarm optimization (MPPSO) technique is applied to the inverse radiation problem in the present paper. The directional radiative intensities are served as the measurement data to estimate the radiative source term, optical thickness, scattering albedo, and phase function in one-dimensional semitransparent plane-parallel media by the inverse simulation. To check the performance and accuracy in retrieval, a comparison is presented between three PSO methods, i.e. the MPPSO, the standard PSO, and the Stochastic PSO. The results confirm the potential of the proposed approach MPPSO and show its effectiveness and superiority over the other two PSO algorithms. Furthermore, the effects of swarm size, searching space, phase change frequency, and velocity-reinitializing frequency on the convergence velocity and computational accuracy of MPPSO are also investigated.     

Modeling of pedestrian evacuation based on the particle swarm optimization algorithm

By applying the evolutionary algorithm of Particle Swarm Optimization (PSO), we have developed a new pedestrian evacuation model. In the new model, we first introduce the local pedestrian’s density concept which is defined as the number of pedestrians distributed in a certain area divided by the area. Both the maximum velocity and the size of a particle (pedestrian) are supposed to be functions of the local density. An attempt to account for the impact consequence between pedestrians is also made by introducing a threshold of injury into the model. The updating rule of the model possesses heterogeneous spatial and temporal characteristics. Numerical examples demonstrate that the model is capable of simulating the typical features of evacuation captured by CA (Cellular Automata) based models. As contrast to CA-based simulations, in which the velocity (via step size) of a pedestrian in each time step is a constant value and limited in several directions, the new model is more flexible in describing pedestrians’ velocities since they are not limited in discrete values and directions according to the new updating rule.     

Modeling the gain and amplified spontaneous emission spectra of erbium-doped fiber amplifiers

We have used a modified “black box” model to calculate the gain and amplified spontaneous emission spectra for an erbium-doped fiber amplifier. Based on this and using an occupation number model, we determined the limiting spectral efficiency of information transfer in such an amplifier. __________ Translated from Zhurnal Prikladnoi Spektroskopii, Vol. 73, No. 2, pp. 273–276, March–April, 2006.     

Impact of the all-optical gain-clamping technique on the transience characteristics of cascaded discrete fiber Raman amplifiers

We theoretically analyse the dynamic response of amplifier cascades involving combinations of unclamped and gain-clamped discrete fiber Raman amplifiers (DFRAs) in the worst possible case of power transients. We consider a 64-channel system in which all of the channels except one (i.e. the surviving channel) are modulated to simulate channel add/drop. We vary the number and the position of the gain-clamped DFRAs in the cascade to determine whether a cascade in which only a few amplifiers are gain-clamped (referred to as a mixed cascade) can be as effective as a cascade comprising all gain-clamped amplifiers for controlling the power transients within tolerable limits (for example, 1 dB). We take into account the location of the surviving channel and the operational regime of the amplifiers. Our results show that the location of the gain-clamped DFRAs in a mixed cascade affects the transient characteristics and that it is possible to control the transients within tolerable limits.     

基于改进粒子群优化算法的火电厂机组负荷分配

以坑口电厂SIS系统机组负荷优化分配功能模块为应用背景,针对基本粒子群优化算法易陷入局部收敛、收敛速度慢的缺点,提出一种基于惯性权重非线性减小策略的改进粒子群优化算法。并且通过MATLAB与Visual C++混合编程,开发了机组负荷在线优化分配功能模块,提高了算法的计算效率和工程应用价值。     

Continuous spatial public goods game with self and peer punishment based on particle swarm optimization

How cooperative behavior emerges and evolves in human society remains a puzzle. It has been observed that the sense of guilt rooted from free-riding and the sense of justice for punishing the free-riders are prevalent in the real world. Inspired by this observation, two punishment mechanisms have been introduced in the spatial public goods game which are called self-punishment and peer punishment respectively in this paper. In each situation, we have introduced a corresponding parameter to describe the level of individual tolerance or social tolerance. For each individual, whether to punish others or whether it will be punished by others depends on the corresponding tolerance parameter. We focus on the effects of the two kinds of tolerance parameters on the cooperation of the population. The particle swarm optimization (PSO)-based learning rule is used to describe the strategy updating process of individuals. We consider both of the memory and the imitation in our model. Via simulation experiments, we find that both of the two punishment mechanisms could facilitate the promotion of cooperation to a large extent. For the self-punishment and for most parameters in the peer punishment, the smaller the tolerance parameter, the more conducive it is to promote cooperation. These results can help us to better understand the prevailing phenomenon of cooperation in the real world.     

液芯光纤方法研究溶剂对分子拉曼光谱强度的影响

液芯光纤可以大幅度提高拉曼光谱强度. 本文用液芯光纤方法测量了CCl4 在CS2 和C6H5Br中不同浓度下459 cm-1,314 cm-1和218 cm-1的拉曼光谱强度,验证了一些溶剂使某些分子拉曼光谱增强的溶剂效应.     

Pump-to-Stokes RIN transfer in Raman fiber lasers and its impact on the performance of co-pumped Raman amplifiers

We show experimentally and numerically that pump-to-Stokes transfer of relative intensity noise (RIN) makes a significant contribution to the output RIN of Raman fiber lasers (RFLs). We theoretically investigate the penalty in the signal-quality factor induced by a noisy RFL pump in a co-pumped Raman-amplified transmission span, where the noise on the RFL output is caused by pump-to-Stokes transfer of RIN. This penalty can be kept low by a proper design of the RFL, in particular by using high-reflectivity output couplers, high-gain Raman fibers and optimizing the RFL fiber length.     

基于PSO和模糊划分熵的水下图像分割

在水下环境中,由于存在着水体对光线的吸收以及照明不均等原因,水下图像具有信噪比低、边缘模糊等特点。如果直接使用传统的分割方法,对水下图像进行处理后的效果较差。传统的基于最大熵原理的阈值法尽管能实现某些特定的分割任务,但是其时效性较差。而粒子群算法(PSO)是一类随机全局优化技术,该算法简单易实现,可调参数少。因此将群体智能中的粒子群优化算法应用到图像分割中。新方法在重新定义模糊熵的基础上,根据最大熵原理,利用粒子群算法来搜索分割阈值。相对于传统的利用穷举法来搜索分割阈值的算法,新方法大大减少了计算时间,提高了效率。通过对水下图像处理实验证明,该算法对简单背景的图像分割是有效的,和传统分割方法相比,具有更强的自适应性和抗噪性能。     

布里渊散射谱参数提取问题的混合优化算法研究与应用

提出了一种将Particle Swarm Optimization(PSO)算法和Levenberg-Marquardt(LM)算法按概率混合优化的新算法,将其用于Pseudo-Voigt型布里渊散射谱以提高其拟合度和频移提取精度。新算法以PSO算法为主框架,首先用PSO算法进行全局搜索,在优化一定次数后每次优化随机产生一个概率rand(0,1),若rand(0,1)小于或等于事先设定的概率P,则把PSO算法得到的最优解作为LM算法的初值进行局部深度搜索,将LM算法得到的最优解替换先前PSO算法的最优解,继续使用PSO算法进行全局搜索;若rand(0,1)大于P则仍然用PSO算法搜索,等待下一次优化产生随机概率rand(0,1)进行判断,交替使用两种算法直至获得理想的全局最优解。仿真分析和实验表明,新算法克服了单一算法的缺点,提高了布里渊散射谱的拟合度和频移提取的精度,充分证明了新算法的实用性和可行性。     

Application of multi-phase particle swarm optimization technique to retrieve the particle size distribution

The multi-phase particle swarm optimization (MPPSO) technique is applied to retrieve the particle size distribution (PSD) under dependent model.Based on the Mie theory and the Lambert-Beer theory, three PSDs, i.e., the Rosin-Rammer (R-R) distribution, the normal distribution, and the logarithmic normal distribution, are estimated by MPPSO algorithm.The results confirm the potential of the proposed approach and show its effectiveness.It may provide a new technique to improve the accuracy and reliability of the PSD inverse calculation.