基于改进DBSCAN算法估计欠定混合矩阵的应用研究  

Application Research of Underdetermined Mixed Matrix Estimation Based on Improved DBSCAN Algorithm

作　　者：王霖郁[1,2] 夏敏 项建弘 WANG Linyu;XIA Min;XIANG Jianhong(College of Information and Communication Engneering,Harbin Engineering University,Harbin 150001,China;Key Laboratory of Advanced Ship Communication and Information Technology,Harbin Engineering University,Harbin 150001,China)

机构地区：[1]哈尔滨工程大学信息与通信学院,哈尔滨150001 [2]哈尔滨工程大学先进船舶通信与信息技术重点实验室,哈尔滨150001

出　　处：《数据采集与处理》2021年第5期969-977,共9页Journal of Data Acquisition and Processing

摘　　要：针对欠定盲源分离(Underdetermined blind source separation,UBSS)问题,采用基于密度的空间聚类(Density based spatial clustering of applications with noise,DBSCAN)算法估计聚类中心时易陷入局部最优,因此由聚类中心坐标构成的混合矩阵的精度降低,导致信号分离结果不理想。本文在DBSCAN基础上提出布谷鸟自适应搜索群优化算法(Cuckoo adaptive search swarm optimization of density based spatial clustering of applications with noise,CASSO-DBSCAN),该算法依据Levy飞行策略增强全局自适应搜索能力,并利用群体学习思想精细寻优得到最优解,从而更加精准地估计聚类中心。通过语音信号的盲源分离仿真实验对该算法进行验证,结果表明,该算法能够有效改善欠定混合矩阵的估计精度,具有良好的鲁棒性,证明了其可行性。Aiming at the issue of underdetermined blind source separation(UBSS),when using the density based spatial clustering of applications with noise(DBSCAN)algorithm to estimate the cluster center,it is easy to fall into the local optimum.Therefore,the accuracy of the mixing matrix composed of the cluster center coordinates is reduced,resulting in unsatisfactory signal separation results.This paper proposes a cuckoo adaptive search swarm optimization based on DBSCAN(CASSO-DBSCAN)algorithm.The algorithm enhances the global adaptive search ability based on the Levy flight strategy,and uses the idea of learning from the group to refine the optimization to obtain the optimal solution,which can estimate the cluster centers more accurately.The paper verifies the algorithm through the simulation of blind source separation of speech signals.Results show that it can effectively improve the estimation accuracy of the underdetermined mixing matrix and has good robustness,which proves the feasibility of the algorithm.

关 键 词：欠定盲源分离 群优化 布谷鸟搜索算法 空间聚类 语音信号 

分 类 号：TN912.3[电子电信—通信与信息系统]