Compare ideal interpolation filter and interpolation by lse fir filter 2
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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).

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

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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)


Kaiser Window & Simulation


Kaiser Window (Simulation)

M+1=55

Alpha=0.5M

Beta


Kaiser Window (Simulation)


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


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


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


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


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


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


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


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


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


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


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


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


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


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


Conclusion


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”.


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