1 / 23

Compare ideal Interpolation filter and interpolation by LSE FIR filter(2)

Compare ideal Interpolation filter and interpolation by LSE FIR filter(2). Advisor : Dr. Yuan-AN Kao Student: Bill Chen. Outline. FIR Filter by Windowing Comparison (Simulation) Conclusion Reference. Design of FIR Filter By Windowing(1/2). Design of FIR Filter By Windowing (1/2).

cameron-adams
Télécharger la présentation

Compare ideal Interpolation filter and interpolation by LSE FIR filter(2)

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Compare ideal Interpolation filter and interpolation by LSE FIR filter(2) Advisor : Dr. Yuan-AN Kao Student: Bill Chen

  2. Outline • FIR Filter by Windowing • Comparison (Simulation) • Conclusion • Reference

  3. Design of FIR Filter By Windowing(1/2)

  4. Design of FIR Filter By Windowing (1/2)

  5. Kaiser Window & Simulation

  6. Kaiser Window (Simulation) M+1=55 Alpha=0.5M Beta

  7. Kaiser Window (Simulation)

  8. Comparison(1/14) Filter coefficient M=55 Interpolation filter by LSE FIR filter Upsample=5 Cutoff freq=0.2pi Passband freq=0.15pi Stopband freq=0.25pi Ideal interpolation filter with Kaiser Window Alpha=0.5*(M-1) Beta

  9. Comparison (2/14) Filter coefficient M=55 Interpolation filter by LSE FIR filter Upsample=5 Cutoff freq=0.2pi Passband freq=0.15pi Stopband freq=0.25pi Ideal interpolation filter with Kaiser Window Alpha=0.5*(M-1) Beta

  10. Comparison (3/14) Filter coefficient M=55 Interpolation filter by LSE FIR filter Upsample=5 Cutoff freq=0.2pi Passband freq=0.1pi Stopband freq=0.3pi Ideal interpolation filter with Kaiser Window Alpha=0.5*(M-1) Beta

  11. Comparison (4/14) Filter coefficient M=55 Interpolation filter by LSE FIR filter Upsample=5 Cutoff freq=0.2pi Passband freq=0.1pi Stopband freq=0.3pi Ideal interpolation filter with Kaiser Window Alpha=0.5*(M-1) Beta

  12. Comparison (5/14) Filter coefficient M=55 Interpolation filter by LSE FIR filter Upsample=5 Cutoff freq=0.2pi Passband freq=0.17pi Stopband freq=0.23pi Ideal interpolation filter with Kaiser Window Alpha=0.5*(M-1) Beta

  13. Comparison (6/14) Filter coefficient M=55 Interpolation filter by LSE FIR filter Upsample=5 Cutoff freq=0.2pi Passband freq=0.17pi Stopband freq=0.23pi Ideal interpolation filter with Kaiser Window Alpha=0.5*(M-1) Beta

  14. Comparison (7/14) Filter coefficient M=11 Interpolation filter by LSE FIR filter Upsample=5 Cutoff freq=0.2pi Passband freq=0.15pi Stopband freq=0.25pi Ideal interpolation filter with Kaiser Window Alpha=0.5*(M-1) Beta0

  15. Comparison (8/14) Filter coefficient M=11 Interpolation filter by LSE FIR filter Upsample=5 Cutoff freq=0.2pi Passband freq=0.15pi Stopband freq=0.25pi Ideal interpolation filter with Kaiser Window Alpha=0.5*(M-1) Beta0

  16. Comparison (9/14) Filter coefficient M=11 Interpolation filter by LSE FIR filter Upsample=5 Cutoff freq=0.2pi Passband freq=0.15pi Stopband freq=0.25pi Ideal interpolation filter with Kaiser Window Alpha=0.5*(M-1) Beta3

  17. Comparison (10/14) Filter coefficient M=11 Interpolation filter by LSE FIR filter Upsample=5 Cutoff freq=0.2pi Passband freq=0.15pi Stopband freq=0.25pi Ideal interpolation filter with Kaiser Window Alpha=0.5*(M-1) Beta3

  18. Comparison (11/14) Filter coefficient M=11 Interpolation filter by LSE FIR filter Upsample=5 Cutoff freq=0.2pi Passband freq=0.15pi Stopband freq=0.25pi Ideal interpolation filter with Kaiser Window Alpha=0.5*(M-1) Beta6

  19. Comparison (12/14) Filter coefficient M=11 Interpolation filter by LSE FIR filter Upsample=5 Cutoff freq=0.2pi Passband freq=0.15pi Stopband freq=0.25pi Ideal interpolation filter with Kaiser Window Alpha=0.5*(M-1) Beta6

  20. Comparison (13/14) Filter coefficient M=11 Interpolation filter by LSE FIR filter Upsample=5 Cutoff freq=0.2pi Passband freq=0.15pi Stopband freq=0.25pi

  21. Comparison (14/14) Filter coefficient M=11 Interpolation filter by LSE FIR filter Upsample=5 Cutoff freq=0.2pi Passband freq=0.15pi Stopband freq=0.25pi

  22. Conclusion

  23. Reference • F.M.Gardner, ”Interpolation in digital modems-Part I :Fundamental” IEEE Trans.Commun.,vol.41 pp.502-508,Mar.1993 • J.V.,F.L.,T.S.,andM.R. ”The effects of quantizing the fractional interval in interpolation filters” • Heinrich Meyr ,Marc Moeneclaey ,Stefan A. Fechtel “Digital Communication Receivers”. New York :Wiley 1997 • C. S. Burrus, A. W. Soewito and R. A. Gopnath, “Least Squared Error FIR Filter Design with Transition Bands,” IEEE Trans. Signal Processing, vol. 40, No. 6, pp.1327-1338, June 1992. • Heinrich Meyr ,Marc Moeneclaey ,Stefan A. Fechtel “Digital Communication Receivers”. New York :Wiley 1997 • Alan V. Oppenheim ,Ronald W. Schafer with John R. Buck “Discrete-Time Signal Processing”.

More Related