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Enhancement of Source Separation Based on Efficient Stone's BSS Algorithm

Ahmed Kareem Abdullah, Chao Zhu Zhang
2014 International Journal of Signal Processing, Image Processing and Pattern Recognition  
An efficient Stone's BSS (ESBSS) algorithm is proposed based on the joint between original Stone's BSS (SBSS) and genetic algorithm (GA).  ...  Performance of the proposed algorithm is first tested through a different pdf source, followed by artifact extraction test for EEG mixtures then compared with the original Stone's BSS (SBSS) and other  ...  Acknowledgements This work was supported by the National Natural Science Foundation of China (Grant No. 61172159) and the Fundamental Research Funds for the central Universities (HEUCFT1101).  ... 
doi:10.14257/ijsip.2014.7.2.39 fatcat:qz6p6al4njg6vnttqaetoi24w4

Blind Source Separation Research Based on the Feature Distance Using Evolutionary Algorithms

Yang Yang, Xiuqin Wang, Di Zhang
2014 International Journal of Acoustics and Vibration  
Experimental results on mixed spoken signals indicated that the established evolutionary algorithm of particle swarm optimization (PSO) and genetic algorithm (GA) could effectively solve the BSS problem  ...  The approach called evolutionary algorithms was used for the BSS problem in this paper.  ...  can be the best solution for solving BSS problems.  ... 
doi:10.20855/ijav.2014.19.4360 fatcat:mamqvcv4uvb5tb5vehpcj7qlxi

A Blind Source Separation Algorithm Based on Dynamic Niching Particle Swarm Optimization

Hongjie Li, Zhen Li, Hongyi Li, S.A. Hamouda, M. Mirzaei, Z. Yu
2016 MATEC Web of Conferences  
The key point is to use the DNPSO rather than particle swarm optimization (PSO) and fast-ICA as the optimization algorithm in Independent Component Analysis (ICA).  ...  The idea of sub-population in DNPSO leads to the greater efficiency compared with other methods when solving high dimensional cost functions in ICA.  ...  In the process of using ICA to solve BSS problem, the choosing of cost function, which estimate the similarity between source signals and separation signals, and the optimization algorithm for determining  ... 
doi:10.1051/matecconf/20166103008 fatcat:plvreboyknagjgez2suq3sj3qm

Bigradient neural network-based quantum particle swarm optimization for blind source separation

Hussein M. Salman, Ali Kadhum M. Al-Qurabat, Abd Alnasir Riyadh Finjan
2021 IAES International Journal of Artificial Intelligence (IJ-AI)  
The abbreviation of the problem is that the ICA needs for optimizing by using one of the optimization approaches as swarm intelligent, neural neworks, and genetic algorithms.  ...  ICA is a statistical approach that depends on the statistical properties of the mixed signals.  ...  The ICA approach is most efficient method to solve the BSS problem. The ICA needs to use and implement some optimization methods as a part of its work.  ... 
doi:10.11591/ijai.v10.i2.pp355-364 fatcat:2hqkpmiwindrfprntzbajrvqly

Blind Image Separation based on a Flexible Parametric Distribution Function

Nouf Saeed
2017 International Journal of Computer Applications  
We use an efficient method based on genetic algorithm and maximum likelihood for estimating the parameters of such score functions.  ...  As a result, many algorithms of feature extraction have been developed for direct application of such image structures.  ...  However, it is difficult to solve this system so, the genetic algorithm (GA) [23] [24] will be used as an alternative numerical method to estimate the parameters.  ... 
doi:10.5120/ijca2017915874 fatcat:e6bfvpwwtfaljj6orp4mpskate

A Novel Fault Diagnosis Method for Rolling Element Bearings Using Kernel Independent Component Analysis and Genetic Algorithm Optimized RBF Network

Hang Dai, Jingshi He
2013 Research Journal of Applied Sciences Engineering and Technology  
Then a RBF network was used to classify the fault patterns. To improve the fault identification, the Genetic Algorithm (GA) was adopted to optimize the parameters of the RBF network.  ...  In the bearing fault diagnosis, the fault feature extraction is also a key issue for successful fault detection.  ...  The concept of the kernel trick allows ICA to be able to solve nonlinear BSS problems, which is very suitable for the case of rolling bearing fault detections.  ... 
doi:10.19026/rjaset.6.4138 fatcat:chni4p23rjeg7lbtpaxhzub2lu

A New Method for Image Noise Removal using Chaos-PSO and Nonlinear ICA

Wei Ding
2011 Procedia Engineering  
The blind source separation (BSS) algorithms, especially the independent component analysis (ICA) algorithms, have been proven to be effective for the image data processing.  ...  A series of experiments have been implemented in this work to validate the efficiency of the proposed method.  ...  The proposed noise removal algorithm RBF based ICA The RBF based ICA is a typical post-nonlinear model (PNL) for nonlinear BSS problem.  ... 
doi:10.1016/j.proeng.2011.11.2611 fatcat:oldhv7fkpjbpjobdvqv7y2u5pa

Simulated Annealing Based-GA Using Injective Contrast Functions for BSS [chapter]

J. M. Górriz, C. G. Puntonet, J. D. Morales, J. J. delaRosa
2005 Lecture Notes in Computer Science  
The new method for blindly separating unobservable independent component signals from their linear mixtures (Blind Source Separation BSS), uses genetic algorithms (GA) to find the separation matrices which  ...  The paper also include a formal prove on the convergence of the proposed algorithm using guiding operators, a new concept in the genetic algorithms scenario.  ...  Of course we used the number of starting points equal to the number of individuals in the genetic generation. 2(b) Conclusions A GGA-based BSS method has been developed to solve BSS problem from the  ... 
doi:10.1007/11428831_72 fatcat:xhhtkz5devd2bpdfug556qpxiu

Enhancing Linear Independent Component Analysis: Comparison of Various Metaheuristic Methods

Nidaa Abbas, Hussein Salman
2020 Iraqi Journal for Electrical And Electronic Engineering  
Many linear and nonlinear ICA methods, such as the radial basis functions (RBF) and self-organizing map (SOM) methods utilise neural networks and genetic algorithms as optimisation methods.  ...  For the contrast function, most of the traditional methods, especially the neural networks, use the gradient descent as an objective function for the ICA method.  ...  The BSS problem can also be solved by using metaheuristic optimisation methods, such as a genetic algorithm (GA) [9] , particle swarm optimisation (PSO) [10] and simulated annealing (SA) [11] algorithms  ... 
doi:10.37917/ijeee.16.1.14 fatcat:6rvoiaa23jgkjb3xdwfxte4j5m

Hybridizing Genetic Algorithms with ICA in Higher Dimension [chapter]

Juan Manuel Górriz, Carlos G. Puntonet, Moisés Salmerón, Fernando Rojas Ruiz
2004 Lecture Notes in Computer Science  
In this paper we present a novel method for blindly separating unobservable independent component signals from their linear mixtures, using genetic algorithms (GA) to minimize the nonconvex and nonlinear  ...  This approach is very useful in many fields such as forecasting indexes in financial stock markets where the search for independent components is the major task to include exogenous information into the  ...  A GGA-based BSS method has been developed to solve BSS problem from the linear mixtures of independent sources.  ... 
doi:10.1007/978-3-540-30110-3_53 fatcat:aqaiuxmu2ney7gjhrra55jpmxa

Blind Source Separation Based of Brain Computer Interface System: A review

Ahmed Kareem Abdullah, Zhang Chao Zhu
2014 Research Journal of Applied Sciences Engineering and Technology  
The study also provides the recent trends and discusses some of a new ideas for BSS techniques in BCI architecture, articles which discussing the BCI system development were analysed, types of the BCI  ...  A lot of refereed journals and conference papers are reviewed and categorized to make this study in useful form. However, there are a few comprehensive reviews of BSS techniques in BCI literature.  ...  Component Analysis (ICA) is a wellestablished technique for BSS.  ... 
doi:10.19026/rjaset.7.280 fatcat:ryzk3k3azbdltoelotmvkfmdj4

Implementation of Optimized Floating Point Ndependent Component Analysis Processor on FPGA for EEG Separation

Jayasanthi Ranjith. M.E, NJR. Muniraj
2012 Journal of Signal Processing Theory and Applications  
For reducing the complexity of ICA algorithms, modularity, hierarchy and parallelism are introduced to ICA in its VLSI implementation.  ...  Independent component analysis (ICA) is a statistical signal processing technique for separating mixed voices, images and signal.  ...  Y.Tan and J.Wang (1991) developed a Genetic Algorithm for Nonlinear Blind Source Separation Using Higher Order Statistics.  ... 
doi:10.7726/jspta.2012.1004 fatcat:qhs5i6kyvnhmjmg3z5f42744zy

Automatic Extraction System for Common Artifacts in EEG Signals Based on Evolutionary Stone's BSS Algorithm

Ahmed Kareem Abdullah, Chao Zhu Zhang, Ali Abdul Abbas Abdullah, Siyao Lian
2014 Mathematical Problems in Engineering  
An automatic artifact extraction system is proposed based on a hybridization of Stone's BSS and genetic algorithm. This hybridization is called evolutionary Stone's BSS algorithm (ESBSS).  ...  The genetic algorithm is a suitable technique to overcome this problem by finding randomly the optimum half-life parameters in Stone's BSS.  ...  Mandic, Imperial College, United Kingdom, for giving them real data (8 channels data); also they express their thanks to Mr. Salim, Wasit University, Iraq, for giving them real data (19 channels).  ... 
doi:10.1155/2014/324750 fatcat:yhjye6lagneppkxvwxb7pgodze

Nonlinear Blind Source Separation for EEG Signal Pre-processing in Brain-Computer Interface System for Epilepsy

D. A.Torse, R. R. Maggavi, S. A. Pujari
2012 International Journal of Computer Applications  
The current study used recently developed source separation method known as "Independent Component Analysis" (ICA) technique for solving blind EEG source separation problem.  ...  The electroencephalogram (EEG) potentials represent the combined effect of potentials from a fairly wide region of the scalp.  ...  There have been some attempts to solve nonlinear BSS problems, especially for separation of image mixtures [32, 33] .  ... 
doi:10.5120/7838-0911 fatcat:56chsaxg45cl3ixdxzqjhkif2q

A Novel Floating Point Fast Confluence Adaptive Independent Component Analysis for Signal Processing Applications

Jayasanthi Ranjith. M.E., Dr.NJR. Muniraj
2013 Advances in Signal Processing  
Fixed point ICA algorithms cover only smaller range of numbers.  ...  Independent component analysis (ICA) is a technique that separates the independent source signals from their mixtures by minimizing the statistical dependence between components.  ...  Fast ICA The Fast ICA Algorithm Due to simplicity and fast convergence, Fast ICA is considered as one of the most popular solutions for linear ICA/BSS problem .The VLSI implementation of this algorithm  ... 
doi:10.13189/asp.2013.010301 fatcat:bvcsxtadfrfzbh6y5pim47epum
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