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So, to reduce the number of samples, we opt for compressive sensing approach. As it is a well-known concept, Compressive Sensing is the framework that mainly depends upon the Sensing matrix for compression and the Basis matrix for representation. By considering this fact, we demonstrate a technique, which is a combination of the Compressive Sensing and BSBL by employing different measurement matrices. Since BSBL has already been mentioned in the literature, we compared the results based on this demonstration with the previously mentioned approach and found a significant change in the parameters mentioned in the result and analysis section. <\/jats:p>","DOI":"10.1142\/s0219691322500370","type":"journal-article","created":{"date-parts":[[2022,8,19]],"date-time":"2022-08-19T03:27:59Z","timestamp":1660879679000},"source":"Crossref","is-referenced-by-count":1,"title":["Effect of sensing matrices on quality index parameters for block sparse bayesian learning-based EEG compressive sensing"],"prefix":"10.1142","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8680-8825","authenticated-orcid":false,"given":"Vivek","family":"Upadhyaya","sequence":"first","affiliation":[{"name":"Department of Electrical and Electronics Engineering, Poornima University, India"}]},{"given":"Mohammad","family":"Salim","sequence":"additional","affiliation":[{"name":"Department of Electronics and Communication Engineering, Malaviya National Institute of Technology, India"}]}],"member":"219","published-online":{"date-parts":[[2022,10,17]]},"reference":[{"key":"S0219691322500370BIB001","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2019.04.013"},{"key":"S0219691322500370BIB002","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2007.4286571"},{"volume-title":"Proc. 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