Tasks to do:

• Deterministic signals and their characteristics
  • Generate periodical harmonic signal with following parameters:
    - amplitude A = 1 , f = 500 Hz , zero phase shift
    - sampling parameters: fs = 8000 Hz , to = 0.1 s (duration time).
  • Observe signal samples of generated signals.
  • Generate sinusoidal with different frequency and sampling frequency and compare the results
    a) fs = 8000 Hz , f = 2000 Hz
    b) fs = 8000 Hz , f = 2123 Hz
    c) fs = 8000 Hz , f = 50 Hz
    d) fs = 1000 Hz , f = 250 Hz

• Stochastic signals and their characteristics
  • Generate a row vector containing white noise of length N = 1000 with following distribution:
    a) uniform distribution (fcn rand),
    b) Gaussian (normal) distribution (fcn randn).
  • Observe distribution of signal samples of generated signals (fcn histogram).
  • Measure basic parameters of generated signals:
    a) mean value (fcn mean),
    b) variance (fcn var),
    c) power (square of signal smaples + fcn mean).
  • Observe and identify above measured values in sample histograms
  • Generate white noise with following parameters:
    a) Gaussian distribution, mean value = 0, variance = 0.1.
    b) uniform distribution, mean value = 0, variance = 0.1,
  • Observe distiribution of the sum of 2 or more (5, 10, 20) realizations of random signals with:
    a) uniform distribution
    b) Gaussian distribution

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• Modeling mixed deterministic and stochastic signal
  • Generate sinusoidal with following parameters:
    - amplitude A = 1 , f = 500 Hz , zero phase shift
    - sampling parameters: fs = 8000 Hz , to = 0.1 s (duration time).
  • Upload speech signal from the file vf3.bin. Its sampling frequency is fs = 16000 Hz ( use function loadbin.m to upload the signal into MATLAB environment )
  • Generate Gaussian white noise with parameters:
    - mean value = 0, variance = 0.4.
    - fs = 8000 Hz , to = 0.1 s (duration time).
  • Add sinusoidal and noise as well as speech signal and noise and compute SNRs (Signal-to-Noise Ration) of these mixtures.
  • Create mixtures with different SNR from above generated signals (SNR = -5, 0, 5, 10, 20)