High performance architectures for block least mean square FIR adaptive filters
| dc.contributor.guide | Mohanty Basant Kumar | |
| dc.coverage.spatial | Electronics and Communication Engineering | |
| dc.creator.researcher | Patel Sujit Kumar | |
| dc.date.accessioned | 2016-11-15T04:26:31Z | |
| dc.date.available | 2016-11-15T04:26:31Z | |
| dc.date.awarded | 21/09/2016 | |
| dc.date.completed | 27/08/2016 | |
| dc.date.registered | 17/07/2012 | |
| dc.description.abstract | Adaptive filters are used in various digital signal processing applications such as noise cancellation echo cancellation, channel equalization and system identification Area delay efficient realization of the adaptive filters has great practical interest for resource constrained DSP applications. The least mean square LMS algorithm based adaptive filters offer low throughput rate and suitable for signals having smaller sampling frequencies. Block LMS BLMS algorithm is a derivative of LMS algorithm which offers L times higher throughput rate than the LMS based adaptive filters and involves nearly L times higher computational newline | |
| dc.description.note | List of Publication | |
| dc.format.accompanyingmaterial | None | |
| dc.format.extent | xiii,132 | |
| dc.identifier.uri | http://hdl.handle.net/10603/120732 | |
| dc.language | English | |
| dc.publisher.institution | Department of Electronics and Communication | |
| dc.publisher.place | Guna | |
| dc.publisher.university | Jaypee University of Engineering and Technology, Guna | |
| dc.relation | 97 | |
| dc.rights | university | |
| dc.source.university | University | |
| dc.subject.keyword | Adaptive Filters | |
| dc.subject.keyword | LMS Algorithm | |
| dc.title | High performance architectures for block least mean square FIR adaptive filters | |
| dc.title.alternative | ||
| dc.type.degree | Ph.D. |
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