摘要
传统的自适应均衡算法存在收敛速度慢、稳定性差、均衡效果不理想等缺点,从而使自适应均衡器在高速光纤通信系统中的应用受到限制.具有梯度搜索因子的Grads-PSO算法,结合了传统数值优化方法在计算速度和计算精度上的优势,将梯度法引入粒子群算法中.在梯度搜索因子的指导下,PSO算法的运算过程显得更加有规则,从而提高了算法的收敛速度和运算精度.因此,本文提出将改进PSO算法用作自适应均衡器均衡算法.通过仿真实验表明,改进PSO算法具有收敛速度快,计算精度高的优点,将其作为自适应均衡器的控制算法可收到很好的均衡效果,优于传统的控制算法.
The traditional adaptive equalization algorithm has some disadvantages, such as slow convergence, poor stability and bad equalization result. These disadvantages restricted the application of adaptive equalizer to the high-speed optical fiber communication systems. The grads particle swarm optimization algorithm that has grads search factor combined the advantages of the traditional numerical optimization methods in calculation speed and calculation accuracy. It introduced the grads method into the particle swarm optimization algorithm. Under the guidance of the grads search factor, the operation process of the particle swarm optimization algorithm is more regular, thereby the convergence speed and calculation accuracy of the algorithm has improved. An algorithm of adaptive equalization based on improved PSO algorithm was presented in this paper. The simulation experiments showed that the improved particle swarm optimization algorithm has many advantages, such as fast convergence, high calculation accuracy. The equalization result of improved particle swarm optimization algorithm is better than the traditional control algorithm.
出处
《河北工业大学学报》
CAS
北大核心
2009年第4期52-55,60,共5页
Journal of Hebei University of Technology
基金
河北省自然科学基金项目(F2008000116)
河北省教育厅自然科学基金项目(2009425)
关键词
粒子群优化算法
改进粒子群优化算法
自适应均衡
自适应均衡算法
光纤通信
particle swarm optimization algorithm
improved particle swarm optimization algorithm
adaptive equali zation
adaptive equalization algorithm
optical fiber communication
