改进PSO-SVM在说话人识别中的应用。通过对粒子群优化算法中惯性权重和全局最优值 的分析，提出了一种根据迭代次数而自适应变化的惯性权重的粒子群优化方法,Improvement in the PSO-SVM speaker recognition applications. Through particle swarm optimization algorithm in the inertia weight and the analysis of the global optimum val

针对标准粒子群算法在进化过程中种群多样性降低而早熟的问题 ,提出一种动态改变惯性权重的自适应粒子群算法.-For PSO population diversity in the evolutionary process and reduce premature problem, a dynamically changing inertia weight adaptive particle swarm optimization.

粒子群算法自适应权重MATLAB程序加注释(AWPSO algorithm MATLAB procedures and notes, demo)