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CONTINUOUS TIME FOURIER SERIES CHAPTER 3.3-3.8 16 CTFS TRANSFORM - PowerPoint PPT Presentation

15 CONTINUOUS TIME FOURIER SERIES CHAPTER 3.3-3.8 16 CTFS TRANSFORM PAIR Suppose () can be expressed as a linear combination of harmonic complex exponentials 0 synthesis equation


  1. 15 CONTINUOUS TIME FOURIER SERIES CHAPTER 3.3-3.8

  2. 16 CTFS TRANSFORM PAIR ο‚‘ Suppose 𝑦(𝑒) can be expressed as a linear combination of harmonic complex exponentials ∞ 𝑏 𝑙 𝑓 π‘˜π‘™πœ• 0 𝑒 synthesis equation ο‚‘ 𝑦 𝑒 = Οƒ 𝑙=βˆ’βˆž ο‚‘ Then the FS coefficients {𝑏 𝑙 } can be found as ο‚‘ 𝑏 𝑙 = 1 π‘ˆ 𝑦(𝑒) 𝑓 βˆ’π‘˜π‘™πœ• 0 𝑒 𝑒𝑒 analysis equation π‘ˆ ∫ ο‚‘ πœ• 0 - fundamental frequency ο‚‘ π‘ˆ = 2𝜌/πœ• 0 - fundamental period ο‚‘ 𝑏 𝑙 known as FS coefficients or spectral coefficients

  3. 17 CTFS PROOF ο‚‘ While we can prove this, it is not well suited for slides. ο‚‘ See additional handout for details ο‚‘ Key observation from proof: Complex exponentials are orthogonal

  4. 18 VECTOR SPACE OF PERIODIC SIGNALS All signals Periodic signals, πœ• 0

  5. 19 VECTOR SPACE OF PERIODIC SIGNALS Periodic signals, πœ• 0 ο‚‘ Each of the harmonic exponentials are orthogonal to 𝑓 π‘˜π‘™πœ• 0 𝑒 each other and span the space 𝑦(𝑒) 𝑏 𝑙 of periodic signals 𝑓 π‘˜2πœ• 0 𝑒 ο‚‘ The projection of 𝑦(𝑒) onto a particular harmonic ( 𝑏 𝑙 ) gives 𝑏 2 the contribution of that 𝑓 π‘˜πœ• 0 𝑒 complex exponential to 𝑏 1 building 𝑦 𝑒 𝑏 0 𝑓 π‘˜0𝑒 = 1 𝑏 βˆ’1 ο‚‘ 𝑏 𝑙 is how much of each harmonic is required to construct the 𝑓 π‘˜(βˆ’πœ• 0 )𝑒 periodic signal 𝑦(𝑒)

  6. 20 HARMONICS ο‚‘ 𝑙 = Β±1 β‡’ fundamental component (first harmonic) ο‚‘ Frequency πœ• 0 , period π‘ˆ = 2𝜌/πœ• 0 ο‚‘ 𝑙 = Β±2 β‡’ second harmonic ο‚‘ Frequency πœ• 2 = 2πœ• 0 , period π‘ˆ 2 = π‘ˆ/2 (half period) ο‚‘ … ο‚‘ 𝑙 = ±𝑂 β‡’ Nth harmonic ο‚‘ Frequency πœ• 𝑂 = π‘‚πœ• 0 , period π‘ˆ 𝑂 = π‘ˆ/𝑂 (1/N period) 1 π‘ˆ 𝑦 𝑒 𝑒𝑒 , DC, constant component, average ο‚‘ 𝑙 = 0 β‡’ 𝑏 0 = π‘ˆ ∫ over a single period

  7. 21 HOW TO FIND FS REPRESENTATION ο‚‘ Will use important examples to demonstrate common techniques ο‚‘ Sinusoidal signals – Euler’s relationship ο‚‘ Direct FS integral evaluation ο‚‘ FS properties table and transform pairs

  8. 22 SINUSOIDAL SIGNAL 1 1 1 4 𝑓 π‘˜2πœ• 0 𝑒 + 𝑓 βˆ’π‘˜2πœ• 0 𝑒 + 2π‘˜ 𝑓 π‘˜3πœ• 0 𝑒 βˆ’ 𝑓 βˆ’π‘˜3πœ• 0 𝑒 ο‚‘ 𝑦 𝑒 = 1 + ο‚‘ 𝑦 𝑒 = 1 + 2 cos 2πœŒπ‘’ + sin 3πœŒπ‘’ Read off coeff. directly ο‚‘ ο‚‘ First find the period ο‚‘ 𝑏 0 = 1 Constant 1 has arbitrary period ο‚‘ ο‚‘ 𝑏 1 = 𝑏 βˆ’1 = 0 cos 2πœŒπ‘’ has period π‘ˆ ο‚‘ 1 = 1 ο‚‘ 𝑏 2 = 𝑏 βˆ’2 = 1/4 𝑏 3 = 1/2π‘˜ , 𝑏 βˆ’3 = βˆ’1/2π‘˜ sin 3πœŒπ‘’ has period π‘ˆ 2 = 2/3 ο‚‘ ο‚‘ 𝑏 𝑙 = 0 , else ο‚‘ ο‚‘ π‘ˆ = 2, πœ• 0 = 2𝜌/π‘ˆ = 𝜌 ο‚‘ Rewrite 𝑦 𝑒 using Euler’s and read off 𝑏 𝑙 coefficients by inspection

  9. 23 PERIODIC RECTANGLE WAVE 1 𝑒 < π‘ˆ 1 ο‚‘ 𝑦 𝑒 = ቐ π‘ˆ 0 π‘ˆ 1 < 𝑒 < 2

  10. 24 SINC FUNCTION ο‚‘ Important signal/function in DSP and communication sin πœŒπ‘¦ normalized ο‚‘ sinc 𝑦 = πœŒπ‘¦ sin 𝑦 unnormalized ο‚‘ sinc 𝑦 = 𝑦 ο‚‘ Modulated sine function ο‚‘ Amplitude follows 1/x ο‚‘ Must use L’Hopital’s rule to get x=0 time

  11. 25 RECTANGLE WAVE COEFFICIENTS ο‚‘ Consider different β€œduty cycle” for the rectangle wave 1 50% (square wave) ο‚‘ π‘ˆ = 4π‘ˆ 1 25% ο‚‘ π‘ˆ = 8π‘ˆ 1 12.5% ο‚‘ π‘ˆ = 16π‘ˆ ο‚‘ Note all plots are still a sinc shape ο‚‘ Difference is how the sync is sampled ο‚‘ Longer in time (larger T) smaller spacing in frequency οƒ  more samples between zero crossings

  12. 26 SQUARE WAVE ο‚‘ Special case of rectangle wave 1/2 𝑙 = 0 with π‘ˆ = 4π‘ˆ ο‚‘ 𝑏 𝑙 = ቐ 1 sin(π‘™πœŒ/2) π‘“π‘šπ‘‘π‘“ ο‚‘ One sample between zero-crossing π‘™πœŒ

  13. 27 PERIODIC IMPULSE TRAIN ∞ ο‚‘ 𝑦 𝑒 = Οƒ 𝑙=βˆ’βˆž πœ€(𝑒 βˆ’ π‘™π‘ˆ) ο‚‘ Using FS integral Notice only one impulse in the interval ο‚‘

  14. 28 PROPERTIES OF CTFS ο‚‘ Since these are very similar between CT and DT, will save until after DT ο‚‘ Note: As for LT and Z Transform, properties are used to avoid direct evaluation of FS integral ο‚‘ Be sure to bookmark properties in Table 3.1 on page 206

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