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基于CPSO-LSSVM的心音身份识别方法

Keywords: 心音信号,身份识别,文化粒子群算法,最小二乘支持向量机,经验模式分解

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Abstract:

提出一种基于文化粒子群算法和最小二乘支持向量机相结合的心音身份识别方法.针对粒子群算法后期收敛速度慢、易陷入局部最优解的缺陷,通过设置文化算法的群体空间和信念空间来加快群体收敛速度.利用经验模式分解将小波包去噪后的心音信号分解成若干个平稳的固有模态分量,然后通过提取主要包含第一、第二心音的固有模态分量,绘制其希尔伯特-黄变换瞬时频谱,计算频谱能量作为特征值,并输入到文化粒子群算法优化的最小二乘支持向量机识别模型中进行分类.测试结果为当λ=28.86、σ=0.87时,CPSO-LSSVM识别模型对3个被测试者120例心音样本的平均识别率为97.7%,较遗传算法、粒子群算法更优,表明了心音身份识别是可行的.

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