Jammer suppression in spread spectrum communication using novel independent component analysis approach

2016 ◽  
Vol 70 (8) ◽  
pp. 998-1005 ◽  
Author(s):  
Jayasanthi Ranjith ◽  
Muniraj
Keyword(s):  
Independent Component Analysis ◽  
Spread Spectrum ◽  
Component Analysis ◽  
Independent Component ◽  
Spread Spectrum Communication ◽  
Analysis Approach

scholarly journals Cancelling ECG Artifacts in EEG Using a Modified Independent Component Analysis Approach

2008 ◽  
Vol 2008 (1) ◽  
Author(s):  
Stéphanie Devuyst ◽  
Thierry Dutoit ◽  
Patricia Stenuit ◽  
Myriam Kerkhofs ◽  
Etienne Stanus
Keyword(s):  
Independent Component Analysis ◽  
Component Analysis ◽  
Independent Component ◽  
Analysis Approach ◽  
Ecg Artifacts

An Independent Component Analysis Approach for Wide-Area Monitoring of Power System Disturbances

2020 ◽  
Vol 48 (6-7) ◽  
pp. 615-627
Author(s):  
José de Jesús Nuño Ayón ◽  
Jorge Luis García Sánchez ◽  
Eduardo Salvador Bañuelos Cabral ◽  
Julián Sotelo Castañón ◽  
María José Rodríguez Roblero
Keyword(s):  
Independent Component Analysis ◽  
Power System ◽  
Component Analysis ◽  
Independent Component ◽  
Wide Area ◽  
Analysis Approach ◽  
Wide Area Monitoring ◽  
Area Monitoring ◽  
Power System Disturbances

Independent Component Analysis Algorithms in Wireless Communication Systems

2009 ◽  
pp. 456-463 ◽  
Author(s):  
Sargam Parmar ◽  
Bhuvan Unhelkar
Keyword(s):  
Independent Component Analysis ◽  
Blind Source Separation ◽  
Antenna Arrays ◽  
Spread Spectrum ◽  
Communication Systems ◽  
Source Separation ◽  
Component Analysis ◽  
Independent Component ◽  
Direct Sequence ◽  
Communication Environment

In commercial cellular networks, like the systems based on direct sequence code division multiple access (DSCDMA), many types of interferences can appear, starting from multi-user interference inside each sector in a cell to interoperator interference. Also unintentional jamming can be present due to co-existing systems at the same band, whereas intentional jamming arises mainly in military applications. Independent Component Analysis (ICA) use as an advanced pre-processing tool for blind suppression of interfering signals in direct sequence spread spectrum communication systems utilizing antenna arrays. The role of ICA is to provide an interference-mitigated signal to the conventional detection. Several ICA algorithms exist for performing Blind Source Separation (BSS). ICA has been used to extract interference signals, but very less literature is available on the performance, that is, how does it behave in communication environment? This needs an evaluation of its performance in communication environment. This chapter evaluates the performance of some major ICA algorithms like Bell and Sejnowski’s infomax algorithm, Cardoso’s Joint Approximate Diagonalization of Eigen matrices (JADE), Pearson-ICA, and Comon’s algorithm in a communication blind source separation problem. Independent signals representing Sub-Gaussian, Super-Gaussian, and mix users, are generated and then mixed linearly to simulate communication signals. Separation performance of ICA algorithms is measured by performance index.

Optimization of an independent component analysis approach for artifact identification and removal in magnetoencephalographic signals

2004 ◽  
Vol 115 (5) ◽  
pp. 1220-1232 ◽  
Author(s):  
Giulia Barbati ◽  
Camillo Porcaro ◽  
Filippo Zappasodi ◽  
Paolo Maria Rossini ◽  
Franca Tecchio
Keyword(s):  
Independent Component Analysis ◽  
Component Analysis ◽  
Independent Component ◽  
Analysis Approach ◽  
Artifact Identification
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