粒子群算法用于盲信号分离的研究

提出一种采用粒子群优化算法进行盲信号分离的新方法,为盲信号分离领域提供一种新的研究思路与方法。该方法采用峰度作为适应度函数,利用粒子群算法对由多个源信号混合而成的信号进行盲信号分离。与自然梯度法盲信号分离相比,粒子群算法精度更高,收敛速度更快,实例仿真成功地对两个图像混合信号进行了盲分离,表明了算法的有效性和优越性。

Application of Particle Swarm Algorithm in Blind Source Separation

A new method of using particle swarm optimization（PSO） algorithm for blind source separation is introduced, which provides a new research idea and method for blind source separation field. The method uses peak as fitness function, and adopts the PSO algorithm to separate blind signals from several source signals. Compared to the natural grad algorithm, the PSO algorithm is better in accuracy and convergence speed, and has more validity.