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https://hdl.handle.net/10356/47031Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Kongara Gangadhar. | en_US |
| dc.date.accessioned | 2011-12-27T05:56:11Z | - |
| dc.date.available | 2011-12-27T05:56:11Z | - |
| dc.date.copyright | 2010 | en_US |
| dc.date.issued | 2010 | - |
| dc.identifier.uri | http://hdl.handle.net/10356/47031 | - |
| dc.description | 90 p. | en_US |
| dc.description.abstract | The polynomial matrix decomposition has many applications in the field of control, but in recent years they have also been used extensively in the area of digital signal processing and communications. Examples include adaptive array signal processing, MIMO and blind source separation. This dissertation tells about polynomial matrix decomposition using plane rotation for estimating the matrix of constant correlation matrix used in the blind source separation. | en_US |
| dc.rights | Nanyang Technological University | en_US |
| dc.subject | DRNTU::Engineering | en_US |
| dc.title | Polynomial matrix decomposition using plane rotation | en_US |
| dc.type | Thesis | en_US |
| dc.contributor.supervisor | Saman S Abeysekera | en_US |
| dc.contributor.school | School of Electrical and Electronic Engineering | en_US |
| dc.description.degree | Master of Science (Signal Processing) | en_US |
| item.grantfulltext | restricted | - |
| item.fulltext | With Fulltext | - |
| Appears in Collections: | EEE Theses | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| EEE_THESES_81.pdf Restricted Access | 8.55 MB | Adobe PDF | View/Open |
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