Blind Signal Separation Algorithm Based on Bacterial Foraging Optimization

被引：0

作者：

Chen, Lei ^{[1
,2
]}

Zhang, Liyi ^{[1
,2
]}

Liu, Ting ^{[1
,2
]}

Li, Qiang ^{[1
]}

机构：

[1] Tianjin Univ, Sch Elect Informat Engn, Tianjin 300072, Peoples R China

[2] Tianjin Univ Commerce, Sch Informat Engn, Tianjin 300134, Peoples R China

来源：

2010 THE 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND INDUSTRIAL APPLICATION (PACIIA2010), VOL V | 2010年

基金：

中国国家自然科学基金;

关键词：

bacterial foraging optimization; blind signal separation; fourth-order cumulant; Givens transform; DISTRIBUTED OPTIMIZATION; BIOMIMICRY;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A novel blind signal separation algorithm based on bacterial foraging optimization was proposed. Fourth-order cumulant of signal was used as objective function for separation and Givens transform method was used for reducing the number of variables in objective function. The bacterial foraging optimization algorithm was used for optimizing the objective function transformed and source signal could be separated from mixed signal. Simulation results show that the separation algorithm based on bacterial foraging optimization can achieve the blind separation successfully and the separation precision is high.

引用

页码：227 / 230

页数：4

共 50 条

[21] An effective bacterial foraging optimizer for global optimization [J].

Zhao, Weiguo ;

Wang, Liying .

INFORMATION SCIENCES, 2016, 329 :719-735

[22] Simplified bacterial foraging optimization with quorum sensing for global optimization [J].

Ben, Niu ;

Qiqi, Duan ;

Hong, Wang ;

Jing, Liu .

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, 2021, 36 (06) :2639-2679

[23] Face Recognition Based on SVM Optimized by the Improved Bacterial Foraging Optimization Algorithm [J].

Zeng, Zhigao ;

Guan, Lianghua ;

Zhu, Wenqiu ;

Dong, Jing ;

Li, Jun .

INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2019, 33 (07)

[24] A Novel Adaptive Chaotic Bacterial Foraging Optimization Algorithm [J].

Zhang, Yuan-tao ;

Zhou, Wei ;

Yi, Jun .

2016 INTERNATIONAL CONFERENCE ON COMPUTATIONAL MODELING, SIMULATION AND APPLIED MATHEMATICS (CMSAM 2016), 2016, :272-279

[25] A survey of bacterial foraging optimization [J].

Guo, Chen ;

Tang, Heng ;

Niu, Ben ;

Lee, Chang Boon Patrick .

NEUROCOMPUTING, 2021, 452 :728-746

[26] Optimization learning of hidden Markov model using the bacterial foraging optimization algorithm for speech recognition [J].

Benmachiche, A. ;

Makhlouf, A. ;

Bouhadada, T. .

INTERNATIONAL JOURNAL OF KNOWLEDGE-BASED AND INTELLIGENT ENGINEERING SYSTEMS, 2020, 24 (03) :171-181

[27] Adaptive computational chemotaxis based on field in bacterial foraging optimization [J].

Xu, Xin ;

Chen, Hui-ling .

SOFT COMPUTING, 2014, 18 (04) :797-807

[28] Underdetermined Blind Source Separation of FSK Signal Based on Particle Swarm Optimization [J].

Xia Jiang-hua ;

Yang Li .

PROCEEDINGS OF THE 2017 7TH INTERNATIONAL CONFERENCE ON ADVANCED DESIGN AND MANUFACTURING ENGINEERING (ICADME 2017), 2017, 136 :209-213

[29] Structural learning of Bayesian networks by bacterial foraging optimization [J].

Yang, Cuicui ;

Ji, Junzhong ;

Liu, Jiming ;

Liu, Jinduo ;

Yin, Baocai .

INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 2016, 69 :147-167

[30] A Bacterial Foraging Optimization Algorithm Based on Normal Distribution for Crowdfunding Project Outcome Prediction [J].

Tan, Yingsi ;

Chen, Shilian ;

Geng, Shuang .

ADVANCES IN SWARM INTELLIGENCE, ICSI 2021, PT I, 2021, 12689 :513-522

← 1 2 3 4 5 →