Daubechies wavelets: Theory and Applications
| dc.contributor.author | Gupta, Kanika | |
| dc.contributor.supervisor | Kavita | |
| dc.date.accessioned | 2019-08-09T08:50:58Z | |
| dc.date.available | 2019-08-09T08:50:58Z | |
| dc.date.issued | 2019-08-09 | |
| dc.description.abstract | The very first tool that strikes in mind for signal processing is fourier transform but its incapability to detect the discontinuity and being localized in time only. Short term fourier transform (STFT) was a improvement to fourier transform. According, to Heisenberg uncertainty principle both frequency and time cannot be measured simultaneously. Therefore, wavelets have proved to be useful enough to analyse the non-stationary signal more accurately incomparison to STFT and fourier transform. Wavelets are useful discovery as it has wide number of applications to name a few are medicine, fingerprint verification. The thesis is a review of Daubechies wavelets with the application in the field of signal processing, partial differential equations (PDE) and applications of wavelets. | en_US |
| dc.identifier.uri | http://hdl.handle.net/10266/5616 | |
| dc.language.iso | en | en_US |
| dc.subject | Wavelets | en_US |
| dc.subject | multi-resolution analysis | en_US |
| dc.subject | correction coefficient | en_US |
| dc.subject | burger's equation | en_US |
| dc.title | Daubechies wavelets: Theory and Applications | en_US |
| dc.type | Thesis | en_US |