Sampling Theorems Periodic Sampling Most signals are continuous
- Slides: 19
Sampling Theorems
Periodic Sampling • Most signals are continuous in time. Example: voice, music, images • ADC and DAC is needed to convert from continuous-time signals to discrete-time signals form and vice-versa.
Periodic Sampling • Periodic Sampling of an analog signal is shown below:
Periodic Sampling • The sampling process Antialiasing filter S/H ADC Digital Processor Reconstruction Filter DAC
Periodic Sampling • Anti-aliasing filter – To prevent aliasing effect – A low-pass analog filter with cut-off frequency less than half of sampling frequency – Pre-filtering to ensure all frequency components outside band-limited signal sufficiently attenuated
Periodic Sampling • Sample-and-hold circuit (S/H) – Samples the input continuous –time signal at periodic intervals – Holds the analog sampled value constant at its output for sufficient time to allow accurate conversion by ADC
Periodic Sampling • Reconstruction Filter – Smooth the staircase-like waveform of DAC output – An analog low-pass filter with cut-off frequency equal half of sampling frequency – Convert x[n] into sequence of impulses and then interpolates to form a continuous-time signal
Periodic Sampling • A simplified representation of sampling process xa(t) Ideal Sampler x[n] Digital processors Ideal Interpolator
Periodic Sampling • x[n] is generated by periodically sampling xa(t) x[n] • Where FT is the sampling frequency
Periodic Sampling xa(t) = A cos (2πFt + φ) xa(t) = A cos (Ωt + φ) Ideal Sampler x[n]=A cos (2πfn + φ) x[n]=A cos (ωn + φ) • where f = F is the relative or normalized frequency of discretetime signal FT ω = ΩT is the relative or normalized angular frequency for discrete-time system
Periodic Sampling • If the continuous-time signal is xa(t)= A cos (Ωt + Φ) where Ω = 2πF (Angular Frequency) • After sampling, the analog signal will become discrete signal in the form of x[n] = xa[n. T] = A cos (Ωn. T + Φ) Since, t = n. T = n FT Then, x[n] = xa[n. T] = A cos (2πFn. T + Φ) = A cos (2πn. F/FT + Φ) = A cos (2πfn + Φ) = A cos (ωn + Φ) Where n is a time index.
Periodic Sampling • Example 1 : The input continuous signal which have frequency of 2 k. Hz enter the DTS system and being sampled at every 0. 1 ms. Calculate the digital and normalized frequency of the signal in Hz and rad. Solution : 1. Calculate the Sampling Rate : FT = 1 / (0. 1 ms) = 10 k. Hz. 2. Now, calculate the digital frequency. f = F / FT = 2 k. Hz / 10 k. Hz = 0. 2 3. The digital frequency in radian, ω = 2πf = 2π (0. 2) = 0. 4π rad. 4. The normalized digital frequency in radian, ω = ΩT = 2πFT = 2π(2 k. Hz)(0. 1 ms) = 0. 4.
Nyquist Sampling & Aliasing • Given a sequence of number representing a sinusoidal signal, the original waveform of the signal (continuous-time signal) cannot be determined • Ambiguity caused by spectral replicating effect of sampling
Nyquist Sampling & Aliasing • Spectral of a bandlimited signal replicate itself at fs period of replication after sampling • Aliasing of replicated signal results in loss of information of the original signal
Nyquist Sampling & Aliasing • Sampling Theorem Let xa(t) be a band-limiting signal with Xa(jΩ) = 0 for | Ω| > Ωm. Then xa(t) is uniquely determined by its samples xa(n. T), -∞ < n < ∞, if ΩT ≥ 2 Ω m (Nyquist Condition/criteria) where ΩT = 2π T
Nyquist Sampling & Aliasing Example 2: If the analog signal is in the form of : xa[t] = 3 cos(1000πt-0. 1π)- 2 cos(1500πt+0. 6π) + 5 cos(2500πt+0. 2π) Determine the signal bandwidth and how fast to sample the signal without losing data ?
Nyquist Sampling & Aliasing Solution : 1. There are 3 frequencies components in the signal which is Ω 1 = 1000π, Ω 2 = 1500π, Ω 3 = 2500π 2. The Input frequencies are : F 1 = Ω 1 / 2π = 500 Hz, F 2 = Ω 2 / 2π = 750 Hz, F 3 = Ω 3 / 2π =1250 Hz 3. Thus the Bandwidth Input signal is : Ω m = 1250 Hz or 1. 25 k. Hz 4. Thus the signal should be sampled at frequency more than twice the Bandwidth Input Frequency, ΩT >2Ωm Thus the signal should be sampled at 2. 5 k. Hz in order to not lose the data. In other words, we need more than 2500 samples per seconds in order to not lose the data
Nyquist Sampling & Aliasing Example 3 : The analog signal that enters the DTS is in the form of : xa[t] = 3 cos(50πt) + 10 sin(300πt) - cos(100πt) a. Determine the input signal bandwidth. b. Determine the Nyquist rate for the signal. c. Determine the minimum sampling rate required to avoid aliasing. d. Determine the digital (discrete) frequency after being sampled at sampling rate determined from c. e. Determine the discrete signal obtained after DTS.
Nyquist Sampling & Aliasing Solutions : a. The frequencies existing in the signals are : F 1 = Ω 1 / 2π = 50π / 2π = 25 Hz. F 2 = Ω 2 / 2π = 300π / 2π = 150 Hz. F 3 = Ω 3 / 2π = 100π / 2π = 50 Hz. Ω m = Maximum input frequency = 150 Hz. b. The Nyquist rate is defined as : 2 Ω m = Ω T = 2(150 Hz) = 300 Hz. c. The minimum sampling rate required to avoid aliasing is Ω T ≥ 2 Ω m = 300 Hz. d. f 1 = F 1 / FT = 25 Hz / 300 Hz = 1/12 f 2 = F 2 / FT = 150 Hz / 300 Hz = 1/2 f 3 = F 3 / FT = 50 Hz / 300 Hz = 1/6 e. The discrete signal after DTS is : x[n] = xa[n. Ts] = 3 cos[2πn(1/12)] + 10 sin[2πn(1/2)]- cos[2πn(1/6)]
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